Founding Simulation Engineer (C++)
Type: Full-time · Founding team Location: Remote-first, async-first Compensation: Competitive salary + founding-team equity
About Nonlimi
Nonlimi is building a cloud-native simulation platform for testing and validating AI agents for autonomous systems — ground robots, drones, and autonomous vehicles.
We're building the simulation infrastructure that robotics startups can't afford to build themselves. Our technical foundation: an open-source ROS2 bridge (Apache 2.0), reproducible version-pinned physics with MuJoCo, and physics-state projection annotations for exact ground truth.
We are pre-revenue and architecture-complete, with a deterministic simulation-and-validation core already shipped — deterministic physics, a scenario/regression runner, the ROS2 bridge, and an annotation pipeline — now in active design-partner scoping.
The Role
You will own the simulation core — the physics engine, sensor simulation, and the bridge between C++ physics and the rest of the platform. This is not a feature team role. The simulation core is the product.
Your work includes:
- Deterministic physics + the regression/replay loop — MuJoCo in deterministic mode (single-threaded, version-pinned, -fno-fast-math), plus the bit-exact replay and baseline-comparison loop that makes simulation usable as CI. This loop is the core of the product.
- Shared-memory IPC — out-of-process ring buffer bridging C++ physics to the platform layer
- ROS2 C++ bridge — native ROS2 integration so customers can use standard tooling (rviz2, rosbag, ros2 topic)
- Sensor simulation + noise/degradation models — LiDAR ray-casting (MuJoCo mj_ray today; Intel Embree on the roadmap) and camera are shipped; you'll deepen them and build the sensor-noise and degraded-signal models (LiDAR, camera, GNSS-denied, IMU) that validation work depends on — feeding physics-state-projection annotations for exact ground truth
- Open-source Nonlimi Core — your work ships under Apache 2.0
Over the first year, you'll extend the core — DART for articulated manipulators, USD pipeline integration, and additional physics domains as new verticals come online.
What You'll Do First
The deterministic core already exists — clone the repo and run nonlimi test scenarios/examples/husky_basic.yaml --output-dir ./artifacts to get a pass/fail verdict and a full artifact bundle in about a second. Your job is to own it and take it from prototype to product: harden the deterministic regression/replay loop, and build the sensor-noise and degraded-signal models the first design-partner proof-of-concept needs. Early on, you'll help land the first measured sim-vs-real correlation result — the evidence that the validation actually predicts hardware behavior.
Requirements
These are hard gates:
- C++ systems engineering, 4–7 years — performance-critical C++ where memory layout, cache behavior, and undefined behavior were first-class concerns
- Physics engine internals — MuJoCo, Bullet3, PhysX, DART, or Gazebo at the integration level — constraint solver configuration, determinism flags, collision shape management
- C++ shared-memory IPC — POSIX SHM, lock-free ring buffers, std::atomic with explicit acquire/release/seq_cst ordering
- Non-determinism debugging — you have found and fixed a case where physics state diverged across runs, across machines, or after a compiler upgrade
Nice to Have
- MuJoCo C API directly (not just mujoco-py or dm_control wrappers)
- ROS2 C++ (rclcpp, DDS transport, composable nodes, lifecycle nodes)
- pybind11 or similar C++/Python binding experience
- Godot 4 or real-time scene graph experience (Unity, Unreal at the renderer level)
- Sim-to-real deployment — taken a policy from simulation to a physical robot
What We Offer
- Competitive salary + founding-team equity — calibrated to seniority and depth of experience
- Full architectural ownership — Nonlimi Core is yours to design, build, and evolve
- Open-source impact — you're building simulation infrastructure the robotics community will use
- Direct customer access — you'll talk to autonomy startups and robotics labs directly
- Remote-first, async-first — deep work is the default
How to Apply
Send us something that demonstrates C++ systems work — a GitHub project, a PR to an open-source project, a Gazebo plugin, a physics engine integration. A strong resume without a code artifact is harder to evaluate; a mediocre resume with compelling code is easier.
After a 30-minute screening call, we'll send a take-home exercise:
Build a minimal SHM ring buffer: C++ producer, Python consumer. 2–4 hours. We're evaluating memory ordering correctness and your written analysis of where you placed acquire/release semantics and why.
[email protected]
Job Type: Full-time
Pay: From 40,000.00€ per year
Work Location: In person
