Founding AI/ML Engineer / Startup / $500k+ / NYC
Open Talent
About the role
Founding AI/ML Engineer / (LLMs / RAG / Agentic Systems) / NYC / $500k+ Equity
We’re hiring for a world class team at one of the fastest growing & most innovative next‑gen aerospace AI companies in North America. They're building LLMs, RAG & high‑performance AI systems to power mission‑critical operations in defence & space.
Only the top 0.1% of America's AI Engineers can do this. If you’ve built real mission critical LLM systems that can’t fail – this could be your next move.
The Role
You’ll own & scale a RAG‑driven AI system powering critical aerospace operations. Expect to tackle retrieval quality, latency bottlenecks, & eval‑driven fine‑tuning head‑on for the most innovative & exciting real‑time systems in Aerospace today. This is full production ownership – from architecture to metrics.
You should have experience with:
- Deploying LLM‑based systems at scale (Llama, Mistral, GPT‑4, Claude)
- Retrieval optimisation – hybrid search (BM25 + vector), reranking, caching
- Evaluation – recall@k, precision@k, groundedness, hallucination metrics
- Fine‑tuning (LoRA/QLoRA), RAG architecture, LangChain / LlamaIndex
- Tooling: Hugging Face, Weaviate/Pinecone, FastAPI, PyTorch, Redis, Postgres
- Monitoring inference, eval automation, & continuous improvement loops
Bonus:
- IoT or Hardware integration or real‑time systems experience exp.
Ideal Background
- CS or Applied ML degree from a top‑tier university
- Proven 0‑1 experience in a fast‑moving AI startup, or Defence related company
- You’ve shipped reliable GenAI systems under pressure
- Degree in Computer Science from a top‑tier university
- Prior experience in high‑performance teams (0‑1, startups)
- You’ve shipped real systems – not demos
Responsibilities
- Own the LLM pipeline end‑to‑end – retrieval → evaluation → fine‑tuning
- Improve accuracy, grounding, and eval metrics continuously
- Make architecture decisions for scale, reliability & speed
- Collaborate directly with founders & domain experts
Stack
- Python / PyTorch / LangChain / Transformers / FastAPI / Hugging Face
- Weaviate / Redis / Postgres / Docker / Kubernetes
Offer
- Up to $500,000+ base salary + equity
- Hybrid in NYC
- Tight‑knit, high‑output team
- High ownership, real impact, flat structure
Interview Process
- Technical Deep Dive
- Technical Assessment or Live Pairing
- Panel focused on mindset & team fit
Equal Opportunity
We’re hiring for an Equal Opportunity Employer.
TL;DR – Senior AI Engineer (NYC, On‑site)
- Build & scale production‑grade GenAI systems from 0 to 1
- Own and improve RAG pipelines – accuracy and latency matter
- Deep experience with LLMs, LangChain, Hugging Face & real deployments
- Must have shipped working GenAI products, not just prototypes
- Ideal: startup DNA, top‑tier CS degree, fast execution mindset
- $500K base + equity
All our new jobs are posted here first:
linkedin.com/in/sufyanbashir/
Requirements
- Deploying LLM-based systems at scale (Llama, Mistral, GPT-4, Claude)
- Retrieval optimisation - hybrid search (BM25 + vector), reranking, caching
- Evaluation - recall@k, precision@k, groundedness, hallucination metrics
- Fine-tuning (LoRA/QLoRA), RAG architecture, LangChain / LlamaIndex
- Tooling: Hugging Face, Weaviate/Pinecone, FastAPI, PyTorch, Redis, Postgres
- Monitoring inference, eval automation, & continuous improvement loops
- Shipped reliable GenAI systems under pressure
- Prior experience in high-performance teams (0-1, startups)
- Shipped real systems - not demos
Responsibilities
- Own the LLM pipeline end-to-end – retrieval → evaluation → fine-tuning
- Improve accuracy, grounding, and eval metrics continuously
- Make architecture decisions for scale, reliability & speed
- Collaborate directly with founders & domain experts
Skills
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