Sr. Simulation Engineer, Physical AI

Investment Profile

Seed-stage infrastructure company in New York building an agentic development platform for the next generation of autonomous physical systems.

The company's AI-native platform helps engineering teams model, validate, test, and continuously improve complex real-world systems in software before deployment. Rather than replacing simulation engines, it orchestrates the engineering workflow surrounding simulation, validation, testing, and continuous improvement, dramatically shortening engineering feedback loops while reducing dependence on expensive real-world testing.

The founding team combines deep expertise across autonomy, AI, distributed systems, and enterprise software, and is assembling an exceptionally technical, in-person engineering team in New York City.

Summary

This isn't a traditional simulation engineering role. It's about building the engineering platform that makes simulation useful.

You'll work across systems engineering, simulation, developer infrastructure, sensing, calibration, validation, performance, and customer engineering. Some weeks you'll build reusable platform capabilities. Others you'll work directly with customers to understand why reality doesn't quite match the model, then turn those learnings into engineering workflows that every future customer can benefit from.

The problems are rarely clean. You'll regularly encounter unfamiliar hardware, noisy sensor data, incomplete information, and ambiguous customer requirements. Success comes from reasoning from first principles, building robust software abstractions, and creating systems that engineers can trust.

If you enjoy difficult technical problems, high ownership, and building foundational infrastructure from scratch, this is one of the most interesting opportunities we've seen in Physical AI.

What You'll Build

• Build reusable platform capabilities for modeling, calibration, validation, and continuous testing.
• Transform messy real-world systems into accurate, production-quality digital representations.
• Design engineering workflows that automate complex simulation, validation, and debugging tasks.
• Improve simulation fidelity, determinism, correctness, scalability, and performance.
• Build developer tooling that dramatically accelerates customer onboarding and engineering iteration.
• Work directly with customers to understand unfamiliar systems, then generalize those learnings into reusable platform capabilities.
• Help define the architecture and technical direction of an agentic development platform for autonomous physical systems.

You'll work closely with the founders and early engineering team across platform engineering, AI infrastructure, simulation, and customer deployments.

What We're Looking For

You likely have experience with several of the following:

• Building robotics, autonomy, perception, simulation, computer vision, or other software systems that interact with the physical world.
• Developing production software in Python (Rust or C++ is a plus).
• Working with physical systems, sensing technologies, calibration, system identification, or quantitative validation.
• Building developer platforms, infrastructure, or internal tooling used by other engineers.
• Shipping production-quality engineering systems rather than research prototypes.
• Operating effectively in ambiguous, fast-moving startup environments.

Experience with robotics simulation platforms, digital twins, physics engines, autonomy stacks, or related technologies is valuable, but we're ultimately looking for exceptional systems engineers who enjoy reasoning about real-world systems, learning unfamiliar domains, and building reusable engineering platforms.

Prior startup experience is a strong plus.

Our ideal candidate has high agency, cares deeply about engineering quality, enjoys working across disciplines, and wants to own difficult technical problems from first principles through production.

About Us

Greylock is an early-stage investor in hu