Job Description

Roles & Responsibilities

AI/ML & GenAI Development

• Design and build machine learning and Generative AI solutions, including RAG pipelines, LLM-based applications, and semantic search

• Develop forecasting and predictive models to support business and product use cases

• Translate business problems into scalable AI/ML solutions

• Work closely with Product and Engineering teams to define and deliver AI-driven features

Model Development & Production

• Own the end-to-end lifecycle of ML models, from experimentation to production readiness

• Ensure models are designed for scalability, reliability, and performance

• Collaborate with ML/AI Engineers to deploy models into production systems

• Apply best practices for model evaluation, monitoring, and improvement

Stakeholder Collaboration

• Work closely with Product, Engineering, and leadership teams to shape AI-driven roadmap decisions

• Communicate complex technical concepts clearly to non-technical stakeholders

• Influence product direction through data-driven insights

• Act as an advocate for Data and AI across the organization

Engineering & Best Practices

• Write maintainable, production-quality Python code

• Apply software engineering best practices (testing, logging, modular design)

• Contribute to improving standards across ML development and deployment

• Support experimentation and proof-of-concepts where needed

Desired Candidate Profile

Qualifications

• 5+ years of experience in Data Science or ML Engineering, with a proven track record of deploying models into production environments

• Hands-on experience with GenAI architectures (RAG), LLM orchestration (LangChain or LlamaIndex), and vector databases (e.g., Pinecone, Qdrant)

• Strong understanding of scalability, reliability, and observability in ML systems

• Solid foundation in statistics, mathematics, and predictive modeling (e.g., forecasting)

• Strong Python skills, with experience writing production-quality code (OOP, testing, logging)

• Experience building APIs using FastAPI or Flask

• Experience with Docker and Kubernetes (AKS)

• Experience working with Microsoft Azure (Azure OpenAI, Azure ML, Azure DevOps)

• Experience collaborating with Engineering Managers and cross-functional teams

• Strong communication skills, with the ability to explain complex topics to non-technical stakeholders

Nice to Have

• Experience fine-tuning open-source LLMs (e.g., Llama, Mistral)

• Experience with information extraction or OCR

• Familiarity with MLOps tools (MLflow, Kubeflow, DVC)

• Background in B2B eCommerce, logistics, or supply chain

• Contributions to open-source projects or a strong technical portfolio