Senior Trainer – Artificial Intelligence & Machine Learning; RAG, Agentic AI & Deployment

Position Summary

We’re looking for an agile and ambitious candidate effective in the qualities listed below within a rapidly growing environment. The ideal candidate will be based near one of our central offices located in this job posting. The role is for a Senior Trainer – Artificial Intelligence & Machine Learning to deliver our advanced AI curriculum focused on LLMs, Retrieval‑Augmented Generation (RAG), Agentic AI, and end‑to‑end deployment.

Experience

Required:

Minimum 4-5 years of professional experience in AI/ML, Data Science, or Applied Machine Learning.

• Deliver engaging, project‑based sessions on advanced topics in AI, LLMs, and agentic AI development.
• Train and mentor learners on:
  • Core AI/ML concepts: supervised & unsupervised learning, deep learning, and NLP.
  • Large Language Models (LLMs): transformer architecture, fine‑tuning, and prompt optimization.
  • Retrieval‑Augmented Generation (RAG): vector databases, document retrieval, embeddings, and knowledge‑grounded responses.
  • Agentic AI Systems: designing and orchestrating AI agents capable of autonomous decision‑making using Lang Graph, CrewAI, or Auto Gen for multi‑agent frameworks; integrating external tools and APIs; understanding memory management and tool use.
  • AI Deployment & MLOps: building scalable APIs with FastAPI or Flask, model packaging with Docker, Kubernetes, CI/CD pipelines, model tracking and monitoring with MLflow, Weights & Biases or Vertex AI Pipelines.
  • Cloud AI Integration: deploying and managing systems on AWS (Sage Maker), Azure ML, or GCP Vertex AI.
• Lead hands‑on projects where learners build RAG‑based chatbots, autonomous AI assistants, and deployed LLM applications.
• Collaborate on curriculum development to integrate cutting‑edge AI research and tools into the training modules.
• Mentor learners through technical challenges, performance optimization, and model deployment.
• Keep up to date with LLM, agentic AI, and generative AI innovations to ensure curriculum relevance.

• 4 to 5+ years in AI/ML engineering, Data Science, Applied NLP or MLOps roles.
• Proficiency in Python and AI libraries such as PyTorch, Tensor Flow, and Hugging Face Transformers.
• Strong experience with LLMs, prompt engineering, and fine‑tuning.
• Practical understanding of RAG systems using Lang Chain and vector databases (e.g. FAISS, Chroma, Pinecone).
• Hands‑on experience in agentic AI frameworks (CrewAI, Auto Gen, Lang Graph, or Lang Chain Agents).
• Knowledge of tool integration, memory management and multi‑agent orchestration.
• Experience deploying AI models with FastAPI, Docker, Kubernetes or cloud‑native tools.
• Familiarity with MLOps pipelines, CI/CD automation and monitoring frameworks.
• Exposure to Generative AI APIs such as OpenAI, Anthropic Claude, Google Gemini or Azure OpenAI.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence or similar technical discipline.
• Excellent communication, mentoring and technical training skills.
• Proven experience conducting technical workshops, bootcamps or corporate AI training programs preferred.
• Ready to deliver on‑site and virtual training.

• Certifications in Machine Learning, Generative AI or Cloud AI services.
• Experience developing autonomous AI agents and multi‑agent ecosystems.
• Working knowledge of vector search optimization, knowledge graph integration and RAG performance tuning.
• Understanding of AI ethics, bias mitigation and responsible AI deployment.
• Enthusiasm for teaching and guiding professionals through hands‑on AI and MLOps implementations.

Revature is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, genetic information, age, marital status, protected veteran status, or disability status.