Machine operator Jobs

Job Description<br><br>Production Engineer (Electrical/Mechanical)"fresh graduates""<br>???? sharkia الصالحية الجديدة <br>We're Hiring | Production Engineer (Electrical /Mechanical)<br><br>We are looking for a Production Engineer to supervise production lines, ensure product quality, improve machine performance, and maintain safe, efficient operations.<br><br>Key Responsibilities:<br><br>Follow up on production plans<br><br>Monitor quality and reduce defects<br><br>Supervise machine operation & troubleshooting<br><br>Coordinate maintenance activities<br><br>Lead and train technicians and operators<br><br>Ensure safety and operational compliance<br><br>Requirements:<br><br>Electrical or Mechanical Engineering background<br><br>Strong problem-solving & leadership skills<br><br>Experience in production/manufacturing is plus<br><br>Full-time availability<br><br>Interested candidates, please send your CV on 01211558519<br><br>Job Details<br><br>Employment Full-time<br><br>Industry<br><br>International Trade and Development

We're Hiring | Service Engineer Location: Egypt Steel Tech is seeking a highly motivated Service Engineer to join our technical team. The successful candidate will be responsible for the installation, commissioning, maintenance, and repair of industrial machinery while delivering exceptional technical support to our customers. Key Responsibilities Install, commission, and test industrial machines at customer sites. Provide customer training on machine operation, maintenance, and safety procedures. Perform preventive and corrective maintenance both on-site and at the company workshop. Diagnose, troubleshoot, and repair electrical, electronic, and control system faults. Repair and test electronic printed circuit boards (PCBs) to ensure reliable machine performance. Prepare technical service reports and maintain accurate service records. Provide technical support to the sales team during customer visits, machine demonstrations, and project evaluations. Ensure high levels of customer satisfaction by delivering timely and professional technical support. Qualifications Bachelor's degree in Engineering. Major in Electronics Engineering is highly preferred; Electrical Engineering or Mechatronics will also be considered.2–6 years of hands-on experience in diagnosing, troubleshooting, and repairing electronic printed circuit boards (PCBs). Strong knowledge of electrical and electronic systems. Excellent analytical and problem-solving skills. Good communication and interpersonal skills. Customer-focused with the ability to work independently and as part of a team. Willingness to travel for customer site visits across Egypt. What We Offer Competitive salary and benefits. Professional training and career development opportunities. Opportunity to work with advanced industrial machinery and cutting-edge technologies. A dynamic and collaborative work environment. If you are passionate about technology, enjoy solving technical challenges, and are looking to advance your career in industrial automation and machinery, we encourage you to apply.

Key Responsibilities Operate and program CNC machines (Turning, Milling, EDM, etc.). Read and interpret technical drawings with high accuracy. Set up machines, tools, and parameters based on specifications. Inspect finished parts to ensure compliance with quality standards. Perform basic machine maintenance and troubleshoot issues. Collaborate with cross-functional teams to improve efficiency and reduce waste.<br>Qualifications Bachelor’s degree in Mechanical, Mechatronics, or Industrial Engineering.1–3 years of experience in CNC operations/programming. Familiarity with CNC control systems (Fanuc, Siemens, Haas). Experience with CAD/CAM software (Solid Works, ESPRIT). Strong attention to detail and problem-solving skills.

Steel Tech which one of well-known suppliers for welding machines, CNC Cutting machines, press brakes , and other machines tools is hiring Presales Engineers to expand team with need for immediate start . Job duties: · Collaborate with management team to craft the company’s vision and mission· search for new clients who might benefit from company products and maximize client potential. · following up with existing customer to enlarge long term relationships and fit their requirements · Achieving a number of daily contacts with customers through phone and emails.· Create Technical Documentation.· prepare technical presentations to demonstrate technical feature of our products.· providing sales support· Participate and preparing for marketing events such as exhibitions and conferences.· Creating and follow up social media campaigns. Job requirements : · Ability to creatively explain and present company product.· Will be preferable to have technical background with understanding in welding and machine tools · Excellent written and verbal communication skills· Excellent presentation and creativity skills· Engineering Bachelor degree · Major ( electronics – electrical , mechatronics , mechanical , Metallurgy )· Experience ( 1 up to 5 years )

Purpose:<br>Support the development, implementation, and maintenance of data science, artificial intelligence, and analytics solutions that enable data-driven decision-making and enhance operational efficiency across the Group.<br>Responsibilities:<br>Work with business stakeholders to understand business requirements and translate them into data-driven solutions, analytical models, and AI-powered products. Develop, implement, and maintain data science, machine learning, and artificial intelligence solutions, including predictive, forecasting, classification, clustering, and anomaly detection models, analytical tools, and business applications that support strategic and operational objectives. Analyse structured and unstructured data to identify trends, patterns, correlations, risks, and opportunities, and provide actionable insights and recommendations to relevant stakeholders. Apply statistical analysis, hypothesis testing, and experimentation techniques to evaluate business problems, validate assumptions, and support data-driven decision-making. Design, develop, and maintain data pipelines, datasets, and support data assets to ensure the availability, quality, integrity, and consistency of information used for analytical and AI solutions. Collaborate with technology and business teams to design, develop, deploy, monitor, and maintain data science solutions, ensuring effectiveness, scalability, and alignment with established technology, information security, and data governance standards. Evaluate the performance and effectiveness of analytical models and AI solutions, establish appropriate success measures, and implement enhancements where required. Research and evaluate emerging technologies, tools, and techniques in data science, artificial intelligence, machine learning, and advanced analytics, and recommend their adoption where appropriate. Ensure compliance with all applicable AML/CTF rules and regulations as required in the conduct of the role. Ensure timely completion of all relevant AML/CTF training provided by the Group. Ensure response to AML, CTF & sanctions inquiries in a timely manner.<br>Job Requirements:<br>Bachelor's degree in Computer Science, Engineering, Information Technology, Data Science, Statistics, Mathematics, or a related field.0 – 2 years’ experience in Data Science, Artificial Intelligence, Machine Learning, Advanced Analytics, or related disciplines. Strong knowledge of statistical analysis, machine learning techniques, predictive modelling, and data mining methodologies. Experience working with Python and relevant data science and machine learning frameworks. Experience working with cloud-based analytics and artificial intelligence platforms, including Azure AI Services or similar technologies. Experience in data preparation, feature engineering, data visualization, and exploratory data analysis. Familiarity with artificial intelligence technologies, including generative AI and large language models. Knowledge of relational and non-relational databases and data management principles. Understanding of software development, system integration, and deployment practices. Excellent communication skills (written, verbal, and listening). Good command of Arabic and English. Able to build partnerships and work well within a team. Ensure deliverables are always of a high quality. Able to prioritize and handle multiple assignments while meeting deadlines.<br>“Thank you for your interest in applying to EFG Holding. Due to the high volume of applications/interest, please note that we are only able to respond directly to applicants that are shortlisted for interviews.”

About Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L<br>Role Overview:We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems. The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.<br>What does day-to-day life look like? Work with real-world ML codebases to support MLE Bench–style evaluation tasks. Build, run, and modify model training, evaluation, and inference pipelines. Prepare datasets, features, and metrics for ML benchmarking and validation. Debug, refactor, and improve production-like ML systems for correctness and performance. Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks. Write clean, reproducible, and well-documented Python code for ML workflows. Participate in code reviews to ensure high standards of engineering quality. Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.<br>Requirements:Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused). Strong proficiency in Python for machine learning and data workflows. Hands-on experience with model training, evaluation, and inference pipelines. Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization). Experience working with ML frameworks (e.g., PyTorch, Tensor Flow, JAX, or similar). Ability to understand, navigate, and modify complex, real-world ML codebases. Experience writing readable, reusable, and maintainable production-quality code. Strong problem-solving and debugging skills. Excellent spoken and written English communication skills.<br>Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. Engagement Type: Contractor assignment (no medical/paid leave) Duration of Contract: 3 months (adjustable based on engagement)<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

About Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L<br>Role Overview:We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems. The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.<br>What does day-to-day life look like? Work with real-world ML codebases to support MLE Bench–style evaluation tasks. Build, run, and modify model training, evaluation, and inference pipelines. Prepare datasets, features, and metrics for ML benchmarking and validation. Debug, refactor, and improve production-like ML systems for correctness and performance. Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks. Write clean, reproducible, and well-documented Python code for ML workflows. Participate in code reviews to ensure high standards of engineering quality. Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.<br>Requirements:Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused). Strong proficiency in Python for machine learning and data workflows. Hands-on experience with model training, evaluation, and inference pipelines. Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization). Experience working with ML frameworks (e.g., PyTorch, Tensor Flow, JAX, or similar). Ability to understand, navigate, and modify complex, real-world ML codebases. Experience writing readable, reusable, and maintainable production-quality code. Strong problem-solving and debugging skills. Excellent spoken and written English communication skills.<br>Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. Engagement Type: Contractor assignment (no medical/paid leave) Duration of Contract: 3 months (adjustable based on engagement)<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

About Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L<br>Role Overview:We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems. The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.<br>What does day-to-day life look like? Work with real-world ML codebases to support MLE Bench–style evaluation tasks. Build, run, and modify model training, evaluation, and inference pipelines. Prepare datasets, features, and metrics for ML benchmarking and validation. Debug, refactor, and improve production-like ML systems for correctness and performance. Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks. Write clean, reproducible, and well-documented Python code for ML workflows. Participate in code reviews to ensure high standards of engineering quality. Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.<br>Requirements:Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused). Strong proficiency in Python for machine learning and data workflows. Hands-on experience with model training, evaluation, and inference pipelines. Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization). Experience working with ML frameworks (e.g., PyTorch, Tensor Flow, JAX, or similar). Ability to understand, navigate, and modify complex, real-world ML codebases. Experience writing readable, reusable, and maintainable production-quality code. Strong problem-solving and debugging skills. Excellent spoken and written English communication skills.<br>Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. Engagement Type: Contractor assignment (no medical/paid leave) Duration of Contract: 3 months (adjustable based on engagement)<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

About Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L<br>Role Overview:We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems. The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.<br>What does day-to-day life look like? Work with real-world ML codebases to support MLE Bench–style evaluation tasks. Build, run, and modify model training, evaluation, and inference pipelines. Prepare datasets, features, and metrics for ML benchmarking and validation. Debug, refactor, and improve production-like ML systems for correctness and performance. Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks. Write clean, reproducible, and well-documented Python code for ML workflows. Participate in code reviews to ensure high standards of engineering quality. Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.<br>Requirements:Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused). Strong proficiency in Python for machine learning and data workflows. Hands-on experience with model training, evaluation, and inference pipelines. Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization). Experience working with ML frameworks (e.g., PyTorch, Tensor Flow, JAX, or similar). Ability to understand, navigate, and modify complex, real-world ML codebases. Experience writing readable, reusable, and maintainable production-quality code. Strong problem-solving and debugging skills. Excellent spoken and written English communication skills.<br>Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. Engagement Type: Contractor assignment (no medical/paid leave) Duration of Contract: 3 months (adjustable based on engagement)<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

About Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L<br>Role Overview:We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems. The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.<br>What does day-to-day life look like? Work with real-world ML codebases to support MLE Bench–style evaluation tasks. Build, run, and modify model training, evaluation, and inference pipelines. Prepare datasets, features, and metrics for ML benchmarking and validation. Debug, refactor, and improve production-like ML systems for correctness and performance. Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks. Write clean, reproducible, and well-documented Python code for ML workflows. Participate in code reviews to ensure high standards of engineering quality. Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.<br>Requirements:Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused). Strong proficiency in Python for machine learning and data workflows. Hands-on experience with model training, evaluation, and inference pipelines. Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization). Experience working with ML frameworks (e.g., PyTorch, Tensor Flow, JAX, or similar). Ability to understand, navigate, and modify complex, real-world ML codebases. Experience writing readable, reusable, and maintainable production-quality code. Strong problem-solving and debugging skills. Excellent spoken and written English communication skills.<br>Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. Engagement Type: Contractor assignment (no medical/paid leave) Duration of Contract: 3 months (adjustable based on engagement)<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

About Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L<br>Role Overview:We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems. The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.<br>What does day-to-day life look like? Work with real-world ML codebases to support MLE Bench–style evaluation tasks. Build, run, and modify model training, evaluation, and inference pipelines. Prepare datasets, features, and metrics for ML benchmarking and validation. Debug, refactor, and improve production-like ML systems for correctness and performance. Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks. Write clean, reproducible, and well-documented Python code for ML workflows. Participate in code reviews to ensure high standards of engineering quality. Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.<br>Requirements:Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused). Strong proficiency in Python for machine learning and data workflows. Hands-on experience with model training, evaluation, and inference pipelines. Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization). Experience working with ML frameworks (e.g., PyTorch, Tensor Flow, JAX, or similar). Ability to understand, navigate, and modify complex, real-world ML codebases. Experience writing readable, reusable, and maintainable production-quality code. Strong problem-solving and debugging skills. Excellent spoken and written English communication skills.<br>Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. Engagement Type: Contractor assignment (no medical/paid leave) Duration of Contract: 3 months (adjustable based on engagement)<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

About Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L<br>Role Overview:We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems. The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.<br>What does day-to-day life look like? Work with real-world ML codebases to support MLE Bench–style evaluation tasks. Build, run, and modify model training, evaluation, and inference pipelines. Prepare datasets, features, and metrics for ML benchmarking and validation. Debug, refactor, and improve production-like ML systems for correctness and performance. Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks. Write clean, reproducible, and well-documented Python code for ML workflows. Participate in code reviews to ensure high standards of engineering quality. Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.<br>Requirements:Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused). Strong proficiency in Python for machine learning and data workflows. Hands-on experience with model training, evaluation, and inference pipelines. Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization). Experience working with ML frameworks (e.g., PyTorch, Tensor Flow, JAX, or similar). Ability to understand, navigate, and modify complex, real-world ML codebases. Experience writing readable, reusable, and maintainable production-quality code. Strong problem-solving and debugging skills. Excellent spoken and written English communication skills.<br>Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. Engagement Type: Contractor assignment (no medical/paid leave) Duration of Contract: 3 months (adjustable based on engagement)<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

About Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L<br>Role Overview:We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems. The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.<br>What does day-to-day life look like? Work with real-world ML codebases to support MLE Bench–style evaluation tasks. Build, run, and modify model training, evaluation, and inference pipelines. Prepare datasets, features, and metrics for ML benchmarking and validation. Debug, refactor, and improve production-like ML systems for correctness and performance. Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks. Write clean, reproducible, and well-documented Python code for ML workflows. Participate in code reviews to ensure high standards of engineering quality. Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.<br>Requirements:Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused). Strong proficiency in Python for machine learning and data workflows. Hands-on experience with model training, evaluation, and inference pipelines. Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization). Experience working with ML frameworks (e.g., PyTorch, Tensor Flow, JAX, or similar). Ability to understand, navigate, and modify complex, real-world ML codebases. Experience writing readable, reusable, and maintainable production-quality code. Strong problem-solving and debugging skills. Excellent spoken and written English communication skills.<br>Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. Engagement Type: Contractor assignment (no medical/paid leave) Duration of Contract: 3 months (adjustable based on engagement)<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

About Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L<br>Role Overview:We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems. The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.<br>What does day-to-day life look like? Work with real-world ML codebases to support MLE Bench–style evaluation tasks. Build, run, and modify model training, evaluation, and inference pipelines. Prepare datasets, features, and metrics for ML benchmarking and validation. Debug, refactor, and improve production-like ML systems for correctness and performance. Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks. Write clean, reproducible, and well-documented Python code for ML workflows. Participate in code reviews to ensure high standards of engineering quality. Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.<br>Requirements:Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused). Strong proficiency in Python for machine learning and data workflows. Hands-on experience with model training, evaluation, and inference pipelines. Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization). Experience working with ML frameworks (e.g., PyTorch, Tensor Flow, JAX, or similar). Ability to understand, navigate, and modify complex, real-world ML codebases. Experience writing readable, reusable, and maintainable production-quality code. Strong problem-solving and debugging skills. Excellent spoken and written English communication skills.<br>Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. Engagement Type: Contractor assignment (no medical/paid leave) Duration of Contract: 3 months (adjustable based on engagement)<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

About Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L<br>Role Overview:We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems. The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.<br>What does day-to-day life look like? Work with real-world ML codebases to support MLE Bench–style evaluation tasks. Build, run, and modify model training, evaluation, and inference pipelines. Prepare datasets, features, and metrics for ML benchmarking and validation. Debug, refactor, and improve production-like ML systems for correctness and performance. Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks. Write clean, reproducible, and well-documented Python code for ML workflows. Participate in code reviews to ensure high standards of engineering quality. Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.<br>Requirements:Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused). Strong proficiency in Python for machine learning and data workflows. Hands-on experience with model training, evaluation, and inference pipelines. Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization). Experience working with ML frameworks (e.g., PyTorch, Tensor Flow, JAX, or similar). Ability to understand, navigate, and modify complex, real-world ML codebases. Experience writing readable, reusable, and maintainable production-quality code. Strong problem-solving and debugging skills. Excellent spoken and written English communication skills.<br>Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. Engagement Type: Contractor assignment (no medical/paid leave) Duration of Contract: 3 months (adjustable based on engagement)<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

About Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L<br>Role Overview:We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems. The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.<br>What does day-to-day life look like? Work with real-world ML codebases to support MLE Bench–style evaluation tasks. Build, run, and modify model training, evaluation, and inference pipelines. Prepare datasets, features, and metrics for ML benchmarking and validation. Debug, refactor, and improve production-like ML systems for correctness and performance. Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks. Write clean, reproducible, and well-documented Python code for ML workflows. Participate in code reviews to ensure high standards of engineering quality. Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.<br>Requirements:Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused). Strong proficiency in Python for machine learning and data workflows. Hands-on experience with model training, evaluation, and inference pipelines. Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization). Experience working with ML frameworks (e.g., PyTorch, Tensor Flow, JAX, or similar). Ability to understand, navigate, and modify complex, real-world ML codebases. Experience writing readable, reusable, and maintainable production-quality code. Strong problem-solving and debugging skills. Excellent spoken and written English communication skills.<br>Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. Engagement Type: Contractor assignment (no medical/paid leave) Duration of Contract: 3 months (adjustable based on engagement)<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

About Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L<br>Role Overview:We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems. The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.<br>What does day-to-day life look like? Work with real-world ML codebases to support MLE Bench–style evaluation tasks. Build, run, and modify model training, evaluation, and inference pipelines. Prepare datasets, features, and metrics for ML benchmarking and validation. Debug, refactor, and improve production-like ML systems for correctness and performance. Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks. Write clean, reproducible, and well-documented Python code for ML workflows. Participate in code reviews to ensure high standards of engineering quality. Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.<br>Requirements:Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused). Strong proficiency in Python for machine learning and data workflows. Hands-on experience with model training, evaluation, and inference pipelines. Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization). Experience working with ML frameworks (e.g., PyTorch, Tensor Flow, JAX, or similar). Ability to understand, navigate, and modify complex, real-world ML codebases. Experience writing readable, reusable, and maintainable production-quality code. Strong problem-solving and debugging skills. Excellent spoken and written English communication skills.<br>Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. Engagement Type: Contractor assignment (no medical/paid leave) Duration of Contract: 3 months (adjustable based on engagement)<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

About Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L<br>Role Overview:We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems. The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.<br>What does day-to-day life look like? Work with real-world ML codebases to support MLE Bench–style evaluation tasks. Build, run, and modify model training, evaluation, and inference pipelines. Prepare datasets, features, and metrics for ML benchmarking and validation. Debug, refactor, and improve production-like ML systems for correctness and performance. Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks. Write clean, reproducible, and well-documented Python code for ML workflows. Participate in code reviews to ensure high standards of engineering quality. Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.<br>Requirements:Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused). Strong proficiency in Python for machine learning and data workflows. Hands-on experience with model training, evaluation, and inference pipelines. Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization). Experience working with ML frameworks (e.g., PyTorch, Tensor Flow, JAX, or similar). Ability to understand, navigate, and modify complex, real-world ML codebases. Experience writing readable, reusable, and maintainable production-quality code. Strong problem-solving and debugging skills. Excellent spoken and written English communication skills.<br>Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. Engagement Type: Contractor assignment (no medical/paid leave) Duration of Contract: 3 months (adjustable based on engagement)<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>We are looking for a highly capable Senior AI Engineer / MLOps Engineer to join our team and lead the design, development, deployment, and optimization of scalable, production-grade AI and machine learning solutions.<br> The ideal candidate will have strong hands-on experience across AI engineering, machine learning, MLOps, cloud-native architecture, and data engineering, with the ability to transform experimentation into reliable, business-ready systems.<br> This role requires deep expertise in LLMs, RAG, agentic AI workflows, CI/CD automation, production ML lifecycle management, and modern data platforms.<br> The selected candidate will be expected to lead end-to-end AI initiatives, work across multiple projects, collaborate with technical and business stakeholders, and ensure operational excellence across AI platforms.<br> Key Responsibilities • Design, develop, deploy, and maintain production-grade AI and machine learning systems end to end.<br> • Build and optimize LLM-powered applications, including RAG pipelines, prompt workflows, agent-based systems, and multimodal AI use cases.<br> • Develop intelligent workflows using tool-calling, orchestration frameworks, and contextual reasoning patterns.<br> • Fine-tune, evaluate, and operationalize machine learning and foundation models for enterprise use cases.<br> • Build and manage MLOps pipelines covering training, evaluation, model registration, deployment, monitoring, and retraining.<br> • Implement CI/CD pipelines for ML and AI workflows to support automated testing, release management, and controlled deployments.<br> • Establish model monitoring frameworks for drift detection, feature attribution, inference quality, and performance tracking.<br> • Ensure reproducibility, reliability, and version control across AI/ML environments.<br> • Architect scalable AI/ML platforms using modern compute, storage, orchestration, monitoring, and search services.<br> • Build repeatable environments using Infrastructure as Code.<br> • Support secure, high-availability, and cost-efficient deployment models across development, staging, and production environments.<br> • Design scalable inference and serving patterns for variable workloads.<br> • Build and maintain automated data pipelines, ETL/ELT workflows, and data processing frameworks for AI/ML consumption.<br> • Ensure data quality, lineage, governance, and versioning to support dependable model training and inference.<br> • Work with structured and unstructured datasets across data lakes, data warehouses, and operational systems.<br> • Deliver analytics-ready datasets to downstream systems and applications.<br> • Lead multiple AI initiatives in parallel, including planning, execution, and coordination with internal teams and stakeholders.<br> • Work closely with product, engineering, data, and business teams to deliver production-ready AI capabilities.<br> • Contribute to architecture decisions, technical documentation, best practices, and engineering standards.<br> • Support knowledge sharing, technical leadership, and continuous improvement across the AI function.<br> • Bachelor’s degree in Computer Engineering, Computer Science, Artificial Intelligence, Data Science, or a related field.<br> • 5+ years of hands-on experience in AI engineering, machine learning engineering, MLOps, or data/ML platform engineering.<br> • Proven experience deploying production AI/ML solutions in enterprise environments.<br> • Strong programming experience in Python and SQL.<br> • Strong experience with enterprise AI/ML architecture and delivery.<br></span> </div>

About Turing:Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L<br>Role Overview:We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems. The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.<br>What does day-to-day life look like? Work with real-world ML codebases to support MLE Bench–style evaluation tasks. Build, run, and modify model training, evaluation, and inference pipelines. Prepare datasets, features, and metrics for ML benchmarking and validation. Debug, refactor, and improve production-like ML systems for correctness and performance. Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks. Write clean, reproducible, and well-documented Python code for ML workflows. Participate in code reviews to ensure high standards of engineering quality. Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.<br>Requirements:Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused). Strong proficiency in Python for machine learning and data workflows. Hands-on experience with model training, evaluation, and inference pipelines. Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization). Experience working with ML frameworks (e.g., PyTorch, Tensor Flow, JAX, or similar). Ability to understand, navigate, and modify complex, real-world ML codebases. Experience writing readable, reusable, and maintainable production-quality code. Strong problem-solving and debugging skills. Excellent spoken and written English communication skills.<br>Perks of Freelancing With Turing:Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.<br>Offer Details:Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. Engagement Type: Contractor assignment (no medical/paid leave) Duration of Contract: 3 months (adjustable based on engagement)<br>After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.<br>Know amazing talent? Refer them at turing.com/referrals, and earn money from your network.