AI/ML Engineer - Professional Services

Exeevo is expanding its Professional Services AI/ML capability to build next-generation data science and agentic AI offerings for Pharma and MedTech clients. We're looking for an AI/ML Engineer who is strong in the fundamentals — probabilities, statistics, ML/DL — and equally excited about modern GenAI, LLMs, and agentic systems on the Microsoft stack. You'll work alongside senior data scientists, architects, and client teams to design and deliver solutions on Azure AI Foundry — hands-on across the full lifecycle, from framing the problem to deploying models and agents into production. What You'll do • 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.

Fundamentals (must-have) • 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. GenAI and Agentic AI • 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. Microsoft and Azure Stack (must-have) • 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. Nice to Have • Exposure to Pharma, Life Sciences, or MedTech data and compliance (HIPAA, GxP). • Deep learning (PyTorch / TensorFlow), OpenTelemetry, or a strong GitHub portfolio. Mindset • 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.