Valleysoft | Center of Excellence is a regional IT services provider based in Riyadh, serving clients globally since 2006.
The company collaborates with global partners like IBM to address diverse business and technical challenges, from enterprise application development to process management.
Valleysoft's vendor-neutral and process-oriented approach, coupled with operational maturity, ensures high-quality and cost-effective services for clients.
As a Data Scientist at Valleysoft, you will play a key role in helping our clients understand complex data, develop analytical models, and derive actionable business insights.
Your expertise in statistical modeling, machine learning, and data analysis will directly contribute to the success of our data-driven initiatives.
The ideal candidate will have a solid background in data science with proficiency in statistical methods and machine learning techniques.
You should possess strong analytical skills and a passion for turning data into impactful insights.
If you're eager to tackle complex problems and contribute to a dynamic team, we would love to hear from you!
Private Health Insurance.
Training & Development.
Competitive salary and benefits package.
Opportunities for professional growth and development in a cutting-edge field.
A collaborative and inclusive work environment.
The chance to work on impactful projects with a team of passionate experts.
Key Responsibilities: LLM Pre-Training & Fine-Tuning: Lead the pre-training of Large Language Models (LLMs) on large-scale datasets, employing cutting-edge techniques to improve model generalization and robustness.
Oversee the fine-tuning of LLMs for specific tasks and applications, ensuring that models are optimized for accuracy, relevance, and performance.
LLM Application Development & Productionisation: Develop and deploy applications leveraging LLMs, from initial concept through to production, ensuring scalability, efficiency, and robustness.
Manage the full lifecycle of LLM application development, including data preparation, model training, evaluation, deployment, and monitoring in production environments.
Agents & Workflow Integration: Design and implement intelligent agent workflows that integrate LLMs into larger AI systems, enabling complex decision-making and task automation.
Collaborate with cross-functional teams to integrate LLM-based agents into existing systems, optimizing performance and user experience.
Generative AI & Advanced Applications: Innovate and implement state-of-the-art Generative AI techniques, such as transfer learning and few-shot learning, to enhance the capabilities of LLMs.
Build advanced LLM-based applications for diverse use cases, including but not limited to text generation, summarization, and conversational AI.
Data Processing & Pipeline Management: Develop and maintain robust data pipelines that ensure the efficient processing, organization, and management of large datasets used in LLM pre-training and fine-tuning.
Work closely with data engineers to ensure seamless data integration and optimal resource utilization throughout the AI/ML lifecycle.
Collaboration & Communication: Collaborate with AI/ML engineers, software developers, product managers, and other stakeholders to bring LLM applications from concept to production.
Communicate complex technical concepts to both technical and non-technical audiences, providing actionable insights and recommendations.
Research & Development: Stay at the forefront of advancements in Generative AI, LLMs, and related fields, applying this knowledge to drive innovation in LLM applications.
Experiment with novel techniques and tools to push the boundaries of what is possible with LLMs and their applications.
Qualifications: Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, Statistics, or a related field.
A Ph.D. is a plus. Experience: 5 - 12 Years Proven experience in data science, AI/ML, with a strong focus on Generative AI and LLMs, including pre-training, fine-tuning, and productionisation.
Demonstrated experience in developing and deploying LLM-based applications, including full lifecycle management from data to production.
Proficiency in Python, TensorFlow, PyTorch, and other relevant ML frameworks.
Technical Skills: Deep understanding of NLP, deep learning, transformer models, and intelligent agent workflows.
Expertise in data preprocessing, feature engineering, and the management of large-scale datasets.
Familiarity with cloud platforms (AWS, GCP, Azure) and MLOps practices.
Soft Skills: Strong analytical and problem-solving skills with the ability to think critically and creatively.
Excellent communication skills, with the ability to present complex ideas clearly.
Ability to work in a dynamic environment, managing multiple projects and priorities.