Senior AI/ML Engineer - LLMs, RAG, Real-Time Aerospace (NYC)
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The role
Own and scale a production-grade LLM pipeline with end-to-end ownership from retrieval to evaluation to fine-tuning.
Tackle retrieval quality, latency bottlenecks, and eval-driven fine-tuning for real-time aerospace operations using hybrid search (BM25 + vector) and reranking.
Implement and operate RAG architectures with LangChain / LlamaIndex, LoRA/QLoRA, and production tooling (PyTorch, FastAPI, Redis, Postgres).
Build and monitor metrics (recall@k, precision@k, groundedness, hallucination) and automate evaluation and continuous improvement loops.
Collaborate directly with founders and domain experts to translate mission requirements into reliable, scalable GenAI systems.
Requirements include shipping production GenAI systems in fast-moving environments; strong CS or Applied ML background; experience with LLMs (GPT-4, Claude, Llama) and related stacks.
Tackle retrieval quality, latency bottlenecks, and eval-driven fine-tuning for real-time aerospace operations using hybrid search (BM25 + vector) and reranking.
Implement and operate RAG architectures with LangChain / LlamaIndex, LoRA/QLoRA, and production tooling (PyTorch, FastAPI, Redis, Postgres).
Build and monitor metrics (recall@k, precision@k, groundedness, hallucination) and automate evaluation and continuous improvement loops.
Collaborate directly with founders and domain experts to translate mission requirements into reliable, scalable GenAI systems.
Requirements include shipping production GenAI systems in fast-moving environments; strong CS or Applied ML background; experience with LLMs (GPT-4, Claude, Llama) and related stacks.
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