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

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🕒 February 16

🌽 Illinois, New Jersey, +1 more states – Remote

🌽 Illinois – Remote 🏖️ New Jersey – Remote 🤠 Texas – Remote

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

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Revature

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

💰 Series A on 2016-03

Revature is a tech engineering services provider with a focus on talent enablement and talent transformation in both bespoke services and enterprise applications. The company works with Fortune 500 companies, government organizations, and top systems integrators to grow their business by providing highly trained Software Engineering teams.

📋 Description

• 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 LangGraph, CrewAI, or AutoGen for multi-agent frameworks. • Integrating external tools, APIs, and reasoning loops for dynamic task execution. • Understanding memory management, context persistence, and tool use in agent frameworks. • AI Deployment & MLOps: Building scalable APIs with FastAPI or Flask. • Model packaging and orchestration with Docker, Kubernetes, and CI/CD pipelines. • Model tracking, experimentation, and monitoring with MLflow, Weights & Biases, or Vertex AI Pipelines. • Cloud AI Integration: deploying and managing systems on AWS (SageMaker), 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.

🎯 Requirements

• 4 to 5+ years in AI/ML engineering, Data Science, Applied NLP, or MLOps roles. • Proficiency in Python and AI libraries such as PyTorch, TensorFlow, and Transformers (Hugging Face). • Strong experience with LLMs, prompt engineering, and fine-tuning. • Practical understanding of RAG systems using LangChain and vector databases (e.g., FAISS, Chroma, Pinecone). • Hands-on experience in agentic AI frameworks (e.g., CrewAI, AutoGen, LangGraph, or LangChain 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, or 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.

🏖️ Benefits

• Professional development opportunities • On-site and virtual training • Flexible work arrangements