Staff ML Engineer, Robot Foundation Models (Defense Manufacturing)

An early-stage robotics company building autonomous machines for American defense manufacturers is hiring staff-level ML engineers to train vision-language-action models. The work is applied rather than pure research, with new systems built from scratch and the chance to put models onto real robots nearly immediately.

Scope

Train and refine VLA models to meet reliability and speed goals for a live customer deployment

Try different data, training recipes and hyperparameters to discover what lifts task success

Build and grow distributed training infrastructure on multi-GPU clusters so experiments move quickly

Own the model lifecycle from assembling datasets through training, evaluation and validation on real robots

Expand experimentation capacity across several workflows as operations grow

Qualifications

Six or more years as a machine learning or robotics engineer, with production-ready ML shipped to physical hardware

Hands-on PyTorch or JAX for training deep learning models

Experience running distributed training on multi-GPU clusters

Familiarity with transformer-based, multimodal or generative models; VLA, VLM or robotics foundation model work is a plus, as is imitation learning or diffusion policies

Ability to own ambiguous projects and deliver working systems; this is not a fit for pure researchers

A degree in computer science, ML, robotics, EE or a related field, or equivalent experience

U.S. citizenship, required for defense work

On-site in New York, NY, with no remote or hybrid option. Unable to consider candidates who need visa sponsorship or transfer.