Machine Learning Engineer with Security Clearance

SynthBee is seeking a Machine Learning Engineer who can take AI models from research to production—integrating agentic AI systems into our product. This role is engineering-focused, working alongside a research counterpart to build and deploy real-world AI automation tools. This is an ideal role for a generalist who has built AI applications before and has strong intuition for AI—especially in deploying AI powered applications and AI agents. At SynthBee we’re building Collaborative Intelligence™ maximizing the potential of people and computers working together.

CI™ will help humans solve the most important scientific, engineering, design, and creative challenges of our time. And create joy in the process. What You’ll Do Develop AI-driven reasoning agents and frameworks for automating complex tasks. Build and optimize RAG (Retrieval-Augmented Generation) pipelines Distill and fine-tune AI models to improve reasoning, automation, and decision-making. Deploy AI models into scalable, production-ready systems using Python and cloud-based infrastructure. Collaborate closely with researchers to operationalize AI advancements into real applications.

What We’re Looking For Proven experience building and deploying AI applications (ideally in a startup or fast-moving environment). Hands-on expertise with agentic frameworks (e.g., AutoGen, CrewAI, LangChain, DSPy, or Haystack). Strong background in AI-powered automation & orchestration workflows. Experience working with vector databases and retrieval systems (e.g., LlamaIndex, FAISS, Pinecone, Weaviate). Some experience with fine-tuning AI models is a big plus, but not required. Solid coding skills in Python, familiarity with cloud deployment tools (AWS, GCP, or Azure). Who Should Apply?

You’ve built AI-powered applications—at a startup, in open-source projects, or in a side hustle. You’re excited about agentic AI and building autonomous workflows that solve real problems. You want to be part of a small, fast-moving team where your work directly impacts the product. You’re comfortable with ambiguity and love figuring things out in a fast-paced startup.