AI/ML Engineer

# Senior Machine Learning Engineer (Generative AI, LLMs, RAG) | Long-Term Contract ## Overview We are looking for an experienced **Machine Learning Engineer** with hands-on expertise in **Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG)** to join our team on a contract basis. You will work on building and deploying production-ready AI solutions across multiple client engagements, including healthcare, enterprise, and other AI-driven applications. ## Responsibilities * Design, build, fine-tune, and evaluate machine learning and LLM-based solutions. * Develop scalable ML pipelines from data ingestion to model deployment and monitoring. * Build and optimize RAG pipelines using vector databases. * Collaborate with solution architects and cross-functional teams to translate business requirements into AI solutions. * Improve model accuracy, latency, scalability, and cost efficiency. * Implement model evaluation, monitoring, guardrails, and observability for production deployments. * Follow MLOps best practices, including model versioning and CI/CD for ML workflows. ## Required Skills * 3–6 years of hands-on experience in Machine Learning Engineering. * Strong Python programming skills. * Experience with PyTorch and/or TensorFlow. * Strong knowledge of scikit-learn. * Hands-on experience with Generative AI and Large Language Models. * Experience with LLM fine-tuning, prompt engineering, and context engineering. * Experience building Retrieval-Augmented Generation (RAG) applications. * Familiarity with vector databases such as Pinecone, Weaviate, Chroma, Milvus, or FAISS. * Understanding of MLOps practices and ML deployment pipelines. * Experience with at least one cloud platform: * AWS SageMaker * Azure Machine Learning * Google Vertex AI ## Nice to Have * Experience in healthcare, HIPAA-compliant solutions, or government technology. * Experience with AI agent or multi-agent orchestration frameworks such as LangGraph, CrewAI, AutoGen, or similar. When applying, please include: 1. Your recent Generative AI/LLM projects. 2. Your experience with RAG and vector databases. 3. Cloud platforms you've worked with. 4. Links to GitHub, portfolio, or relevant case studies (if available).