Robotics ML Scientist: Production Systems & Physical AI

Empathy Talent; New York (NY); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Equity

Job summary

Empathy Talent in New York City is seeking a versatile ML engineer to advance robot learning and deploy intelligent systems in production warehouses. The role blends research with production, requiring deep hands-on coding and collaboration with robotics and deployment teams.

You will train models, optimize them for edge hardware, build data pipelines, and evaluate new approaches, contributing to a fast-moving startup that ships impactful automation technology.

Qualifications

• Experience deploying ML models in production environments.
• Proficient in PyTorch, TensorFlow, or Ray.
• Strong production-grade coding ability.
• Experience across the ML lifecycle from research to deployment.
• Ability to work autonomously in a fast-moving startup.
• Generalist mindset across ML and robotics stack.
• Passion for robotics, AI, and physical automation.

Responsibilities

• Improve how quickly and reliably robotic systems learn and perform new tasks.
• Train vision-language-action models for robotic grasping, manipulation, and control using datasets.
• Evaluate new robot learning approaches and apply promising methods to production systems.
• Build data pipelines for data collected by deployed robots.
• Optimize neural networks for large-scale training and edge inference.
• Integrate trained models into the production robotics stack.
• Collaborate with robotics and deployment teams to scale performance across environments.

Skills

ML in production

PyTorch

TensorFlow

Ray

Production code

ML lifecycle

Embedded systems

Education

Master's degree in CS/ML/Robotics

Tools

ROS2

Simulation environments

Edge hardware

Job description

Empathy Talent in New York City is seeking a versatile ML engineer to advance robot learning and deploy intelligent systems in production warehouses. The role blends research with production, requiring deep hands-on coding and collaboration with robotics and deployment teams.

You will train models, optimize them for edge hardware, build data pipelines, and evaluate new approaches, contributing to a fast-moving startup that ships impactful automation technology.