Lead ML Engineer — Build LLMs & MVPs for AI Platform

People In AI; New York (NY); On-site; USD 500,000 - 700,000; Full time

Job summary

People In AI in New York, NY is seeking a Lead Machine Learning Engineer to join a greenfield AI function with direct access to senior leadership. You will prototype and scale AI solutions, including fine‑tuning LLMs, building embeddings, and MVPs from scratch.

You will own end‑to‑end projects, collaborate across teams to solve high‑value business problems, evaluate AI vendors, and help define infrastructure and tooling standards for production systems.

Qualifications

• Strong CS fundamentals; advanced degree preferred or equivalent practical expertise.
• Proven track record fine‑tuning models and building AI solutions beyond API integrations.
• Python fluency with production experience using PyTorch and Hugging Face.
• End‑to‑end ownership of projects in fast‑paced or high-stakes environments.
• Exposure to NLP, embeddings, or visual models in real-world settings.

Responsibilities

• Build, fine‑tune and deploy LLMs and custom embedding models.
• Own full‑stack prototypes that evolve into operational tools.
• Collaborate across functions to solve high‑value business problems using AI.
• Evaluate and integrate AI/ML vendors and tools, setting standards from the ground up.
• Tackle complex, unstructured data problems and deliver elegant solutions.
• Be a founding force — your success may pave the way for growing the AI function.

Skills

CS fundamentals

Fine-tuning models

Python

PyTorch

Hugging Face

End-to-end ownership

NLP/embeddings

Education

Advanced degree preferred

Tools

PyTorch

Hugging Face

Job description

People In AI in New York, NY is seeking a Lead Machine Learning Engineer to join a greenfield AI function with direct access to senior leadership. You will prototype and scale AI solutions, including fine‑tuning LLMs, building embeddings, and MVPs from scratch.

You will own end‑to‑end projects, collaborate across teams to solve high‑value business problems, evaluate AI vendors, and help define infrastructure and tooling standards for production systems.