Machine Learning Engineer

• Design and build end-to-end ML pipelines (data ingestion * feature engineering * model training * deployment * monitoring)
• Develop and deploy LLM / GenAI solutions (RAG, NLP, prompt engineering, vector search)
• Work with large, complex structured and unstructured datasets
• Build scalable, production-ready services using modern cloud infrastructure
• Partner with stakeholders to translate real business problems into ML solutions
• Implement model monitoring, drift detection, and retraining strategies

This is a full-time, direct hire position (no C2C) working on real-world systems that require scalability, reliability, and measurable business impact-not experimental or research-only work.

• Must have hands-on experience building and deploying ML systems in production
• Must have experience working with sensitive, regulated, or compliance-driven data environments
• No third-party submissions / no C2C, * 5+ years of experience as a Machine Learning Engineer (not just Data Scientist/Analyst)
• Strong experience with Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn)
• Hands-on experience with:

• ML pipelines / MLOps (CI/CD, model deployment, monitoring)
• Cloud platforms (AWS, Azure, or Google Cloud Platform)
• Containerization (Docker, Kubernetes preferred)

• Experience with GenAI / LLMs (RAG, embeddings, vector databases, LangChain, etc.)
• Experience working with regulated or high-sensitivity data environments (financial, healthcare, gov, etc.)
• Strong communication skills and ability to work cross-functionally