ML Engineer

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. #J-18808-Ljbffr