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Mid-level ML role with niche LLM requirements reduces applicant pool despite metro location and common title.
Highly specialized LLM and ML production experience limits transferability across unrelated industries.
Explicit 5-8 years, mandatory LLM production experience, and specific tech stack make filters stringent.
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Build, evaluate, and ship AI/ML models focused on agentic systems and large language models (LLMs) in production environments.
Translate complex business problems into ML solutions and collaborate cross-functionally with product and engineering teams to measure outcomes.
Implement and manage LLM and agentic systems using APIs such as Gemini, OpenAI, or Anthropic with features like streaming and tool use.
5-8 years of software engineering experience including at least 1 year working with production LLM/agentic systems.
Strong proficiency in Python 3.10+ including FastAPI, asyncio, and structured logging.
Hands-on experience with Gemini, OpenAI, or Anthropic APIs and production agent frameworks like LangChain, LangGraph, or AutoGen.
Experience with vector databases (e.g., FAISS, Pinecone), embedding pipelines, and understanding of distributed systems architectures.
Experienced in shipping and scaling AI/ML solutions specifically involving LLMs and agentic system frameworks in production.
Skilled in prompt engineering best practices such as versioning, A/B testing, and use of golden data sets to improve model performance.
Comfortable working within event-driven, distributed system environments leveraging message queues and design patterns ensuring idempotency.