Senior ML Systems Engineer — Autonomous Physical Platforms

Greylock Partners; New York (NY); On-site; USD 140,000 - 230,000; Full time

Job summary

Greylock Partners is building an in-person, seed-stage infrastructure platform in New York. You will help create ML systems that enable engineers to model, validate, test, and continuously improve complex physical systems before real-world deployment.

You will work at the intersection of machine learning, simulation, sensing, system identification, validation, and developer infrastructure. The role blends ML with software engineering to narrowly focus on production-grade outcomes in a fast-paced

Qualifications

• Experience building production ML systems using Python and modern ML frameworks such as PyTorch or JAX.
• Experience modeling and working with complex numerical, temporal, spatial, sensor, or scientific data.

Responsibilities

• Build ML systems that help engineers understand, predict, and improve complex physical systems.
• Develop surrogate and learned models that approximate expensive physical processes.
• Create data and training pipelines combining simulated and real-world observations.
• Collaborate with customers to generalize learnings into reusable ML capabilities.

Skills

Python

PyTorch

JAX

ML systems

Robotics

Autonomy

Simulation

Active learning

Optimization

Reinforcement learning

Tools

PyTorch

JAX

Python

Job description

Greylock Partners is building an in-person, seed-stage infrastructure platform in New York. You will help create ML systems that enable engineers to model, validate, test, and continuously improve complex physical systems before real-world deployment.

You will work at the intersection of machine learning, simulation, sensing, system identification, validation, and developer infrastructure. The role blends ML with software engineering to narrowly focus on production-grade outcomes in a fast-paced