Founding ML Engineer / Series A / NYC / $250k + Founding Equity
Open Talent
About the role
Founding AI/ML Engineer (Production) - NYC - $250k-$500k+ + Founding Equity
We’re hiring for one of NYC’s top 10 robotics startups. If you’re an elite engineer looking to join an A squad-builders from SpaceX, Palantir, Google & Anduril - this is where you want to be.*
Most AI roles are currently focused on generating pixels or text. This team are using LLMs to command multi-ton autonomous machines.
Must be based in NYC & role requires US citizenship due to regulatory constraints.
We need a Founding AI/ML Engineer to build the production intelligence layer for autonomous heavy machinery. This isn't a research lab. We have real robots, real customers, and systems operating in the field 24/7. Your work won't just generate tokens; it will drive physical outcomes.
The Work
This is a 100% production role focused on critical AI infrastructure. You are responsible for the intelligence that allows multi-ton machines to act on complex environments. • Production LLMs: Fine-tuning and deploying models that handle mission-critical operational logic. • Systems & Infra: Building the RAG pipelines and data flywheels that power our fleet’s intelligence. • Evals & Determinism: Designing evaluation frameworks to ensure model outputs are safe and reliable enough for heavy hardware. • Problem Solving: Moving from raw telemetry to deployed models. You own the pipeline, the tuning, and the performance in the field.
The Team
You’ll be joining a high-density team from SpaceX, Palantir, and Anduril. We’ve stripped away the typical corporate friction-no bloated meetings or research for the sake of research. We hire for high agency and low ego. As a founding hire, you aren't just training models; you’re architecting the intelligence of the company.
What we're looking for
We want high-signal builders who are bored with "wrapper" apps and want to solve hard problems grounded in physics. • Production Grit: You’ve shipped ML systems at scale. You care about inference latency and reliability more than "vibe checks." • LLM Mastery: Deep experience with fine-tuning, RAG, and prompt engineering in high-stakes environments. • Systems Thinker: You understand the full stack. You know how to optimize models to run efficiently and how to build the infra that supports them. • High-Bar Pedigree: You’ve worked in environments where the standard for "production-ready" is exceptionally high.
Stack & Comp • Stack: Python, PyTorch, LLMs, RAG, Vector DBs, Kubernetes. • Location: NYC (Manhattan) - On-site/Hybrid. • Comp: $250k - $500k+ base + Founding Member Equity.
The Process:
1 Week & 0 Take-Homes We move as fast as we ship. We can go from first touch to offer in one week: • (Founders) Technical Deep Dive: A conversation about the most complex AI system you’ve actually shipped. • (Team)Practical Pairing: Solving a real-world production ML or data infra problem together. No Leetcode. • (Exec) Founding Team Chat: A focus on judgment, trade-offs & vision.
If you’re ready to put AI into the physical world, let’s talk.
TL;DR • Role: Founding AI/ML Engineer (Production) • Focus: Fine-tuning, Evals, and RAG for Robotics • Team: Ex-SpaceX, Palantir, Anduril, Google • Comp: $250k - $500k+ base + Founding Equity • Process: 1 week. 3 rounds.
Equal Opportunity
We're hiring for an Equal Opportunity Employer. • All our new jobs are posted here 1st:
linkedin.com/in/sufyanbashir/
Requirements
- We want high-signal builders who are bored with "wrapper" apps and want to solve hard problems grounded in physics
- You care about inference latency and reliability more than "vibe checks."
- LLM Mastery: Deep experience with fine-tuning, RAG, and prompt engineering in high-stakes environments
- Systems Thinker: You understand the full stack
- You know how to optimize models to run efficiently and how to build the infra that supports them
- High-Bar Pedigree: You’ve worked in environments where the standard for "production-ready" is exceptionally high
- Stack & Comp
- (Founders) Technical Deep Dive: A conversation about the most complex AI system you’ve actually shipped
- (Team)Practical Pairing: Solving a real-world production ML or data infra problem together
- No Leetcode
Responsibilities
- Most AI roles are currently focused on generating pixels or text
- You are responsible for the intelligence that allows multi-ton machines to act on complex environments
- Production LLMs: Fine-tuning and deploying models that handle mission-critical operational logic
- Systems & Infra: Building the RAG pipelines and data flywheels that power our fleet’s intelligence
- Evals & Determinism: Designing evaluation frameworks to ensure model outputs are safe and reliable enough for heavy hardware
- Problem Solving: Moving from raw telemetry to deployed models
- You own the pipeline, the tuning, and the performance in the field
- Production Grit: You’ve shipped ML systems at scale
- Stack: Python, PyTorch, LLMs, RAG, Vector DBs, Kubernetes
- (Exec) Founding Team Chat: A focus on judgment, trade-offs & vision
- Focus: Fine-tuning, Evals, and RAG for Robotics
Benefits
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