We are looking for a skilled Machine Learning Engineer with hands-on experience in Agentic AI systems and Generative AI to join our growing AI team.

Role: Machine Learning Engineer

Location: remote United States

4+ years of dedicated experience in Agentic AI and/or Generative AI (LLMs, RAG, agents, prompt engineering)
4+ years of prior experience as a Python Engineer / Python Developer (before or alongside ML work)

Strong proficiency in Python — packaging, async programming, API design
Hands-on experience with at least one agentic framework: LangGraph, LangChain, AutoGen, CrewAI, or similar
Experience with OpenAI, Anthropic, or open-source LLM APIs
Solid understanding of ML fundamentals — supervised/unsupervised learning, model evaluation, feature engineering
Familiarity with vector databases (Pinecone, Weaviate, Chroma, FAISS) and embedding models
Experience with REST API development and microservices architecture

Design and develop agentic AI systems using frameworks such as LangGraph, LangChain, AutoGen, or CrewAI
Build, fine-tune, and deploy large language model (LLM) based solutions including RAG pipelines, tool-calling agents, and multi-agent workflows
Integrate LLMs with external tools and APIs via MCP (Model Context Protocol), function calling, or custom orchestration layers
Develop and maintain ML pipelines for training, evaluation, and production serving
Write clean, production-grade Python code following software engineering best practices
Collaborate with product, data engineering, and backend teams across the full SDLC
Monitor model performance in production and implement feedback loops for continuous improvement
Contribute to architectural decisions around AI system design, scalability, and cost optimization

Experience with MCP (Model Context Protocol) or tool-use / function-calling patterns
Exposure to MLOps tooling — MLflow, Weights & Biases, SageMaker, or similar
Knowledge of cloud platforms (Azure, AWS, or GCP) for model deployment
Familiarity with FastAPI / Flask for serving ML models
Experience with multi-modal models (vision-language, speech)

Tech Stack (Typical): Python · LangChain / LangGraph · OpenAI / Anthropic APIs · FastAPI · PostgreSQL / MongoDB · Docker · Git · Vector DBs · Cloud (AWS/GCP/Azure)

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