  Build end-to-end ML and data science pipelines on Azure — ingestion, feature engineering, training, evaluation, and deployment.

Develop LLM-powered solutions including RAG pipelines, prompt-engineered workflows, and agentic systems using Microsoft Agent Framework, Semantic Kernel, and Azure AI Foundry.
Work with Pharma and MedTech data — commercial, clinical, real-world evidence, HCP/HCO, patient journey — to deliver predictive and generative use cases.
Implement and integrate MCP tools and A2A-style agent collaboration patterns into client offerings.
Operationalize models and agents using Azure ML and Azure AI Foundry — versioning, monitoring, observability, and responsible-AI guardrails.
Collaborate with client stakeholders to translate business problems into solutions and contribute to POCs and proposals.

  Bachelor's or Master's in CS, AI/ML, Data Science, Statistics, Applied Math, or a related quantitative field.

Strong foundation in mathematics, probability, statistics, and linear algebra.
Solid grasp of classical ML — regression, classification, clustering, tree-based models, evaluation, cross-validation.
Proficient in Python (NumPy, pandas, scikit-learn) and working knowledge of both SQL and NoSQL.
Hands-on exposure to LLMs and GenAI — prompt engineering, embeddings, vector stores, RAG.
Familiarity with at least one agentic framework (Microsoft Agent Framework, Semantic Kernel, LangChain/LangGraph) and awareness of MCP and A2A protocols.
Experience with Azure AI Foundry, Azure OpenAI, or Azure ML — via coursework, internships, projects, or prior work.
MLOps basics — experiment tracking, model registry, CI/CD, Docker, Git.
Exposure to Pharma, Life Sciences, or MedTech data and compliance (HIPAA, GxP).
Deep learning (PyTorch / TensorFlow), OpenTelemetry, or a strong GitHub portfolio.
Curiosity and a fast-learning curve — this field moves quickly.
First-principles thinking and clear communication with clients and peers.
Ownership and a pragmatic engineering mindset — production-ready, not notebook-only.

  Real, production-grade AI work for leading Pharma and MedTech clients from day one.

Mentorship from senior architects and exposure across classical ML, GenAI, agentic AI, and MLOps on Azure.
Hybrid work, a learning-first culture, and support for Azure certifications.

AI/ML Engineer – Professional Services

Key skills