Founding AI/ML Engineer / Startup / $500k+ / NYC
Role summary
This role is for a Founding AI/ML Engineer in a fast-growing aerospace AI startup in NYC. The engineer will own and scale a RAG-driven AI system for mission-critical defense and space operations. Responsibilities include end-to-end pipeline management, from retrieval and evaluation to fine-tuning, focusing on accuracy, grounding, and latency. The role requires deploying LLM-based systems at scale, optimizing retrieval, and implementing robust evaluation metrics. Experience with tools like LangChain, Hugging Face, and vector databases is essential, along with a proven track record of shipping production-grade GenAI systems, ideally in a startup or defense context. The position offers a hybrid work model and significant ownership.
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
You’ll be expected to:
- 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:
1) Technical Deep Dive
2) Technical Assessment or Live Pairing
3) Panel focused on mindset & team fit
Equal Opportunity
We're hiring for an Equal Opportunity Employer.
If you’ve shipped real GenAI systems, thrive under pressure, and want to see your models
power live aerospace systems
- this is where theory meets orbit.
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
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