Senior Software Engineer, Rendering Infrastructure (AV Simulation)

Job description

Job responsibilities

• Connect the renderer to AV software stacks and compute clusters — designing low-latency, high-bandwidth transport using ROS/ROS 2, shared-memory IPC, gRPC, and sockets with appropriate serialization formats, and…
• Integrate the renderer with learned driving models through Gymnasium-style environment APIs — stepping the simulation from Python, exchanging observations and actions efficiently with PyTorch-based models, and…
• Integrate the runtime with the cloud and on-premises execution environments used for large-scale closed-loop testing, continuous integration, and perception training pipelines.
• Improve and validate deterministic execution — establishing the required bit-accurate or frame-deterministic lock-step behavior across the simulation clock, dynamic physics updates, and the ray-traced renderer, and…
• Reproduce real sensor scheduling and vehicle timing — staggered camera exposures, rolling shutter behavior, LiDAR spin and packet rates, hardware clock drift, and the onboard constraints perception actually operates…
• Build perturbation mechanisms that inject timing jitter, dropped or out-of-order frames, and calibration drift in both extrinsics and intrinsics, and use them to stress-test downstream perception and sensor fusion…
• Build memory-efficient multi-world and multi-scenario execution inside a single rendering process, using shared geometry and instancing — OptiX IAS/GAS, or the analogous acceleration structure hierarchies in Vulkan/DXR…
• Optimize GPU memory footprint, scene streaming, and execution scheduling to maximize frames per second per GPU across concurrent simulation workers.

Job requirements

• Bachelor's degree in Computer Science, Computer Engineering, a related technical field, or equivalent practical experience.
• 5+ years of professional software engineering experience, with a substantial portion focused on performance-critical systems software.
• Production proficiency in modern C++ (C++17/20), including performance optimization, memory management, and clean API and system design in a large codebase, plus working proficiency in Python for tooling and automation.
• Strong Linux systems programming foundation: multithreading and concurrency, memory management, IPC, and high-throughput data movement, including systems that operate across process and machine boundaries.
• Depth in at least one of the two domains this role bridges, and the interest to grow into the other: Robotics or autonomous systems — the architecture and integration of perception, planning, or control components, and…
• GPU programming through a compute or ray tracing API (CUDA, OptiX, Vulkan, DXR, or similar), with a working understanding of GPU memory and execution models.
• A track record of designing, implementing, and debugging reliable distributed systems, including the nondeterminism and failure modes that come with them.
• Experience profiling and optimizing real systems, and the instinct to measure before optimizing.