
Senior Software Engineer, Rendering Infrastructure
Posted 2 days ago

Posted 2 days ago
This is a fully remote position, open to applicants in California.
• Develop large-scale production systems for a GPU-accelerated, physically-based simulator for autonomous vehicle sensors.
• Link the renderer with autonomous vehicle software stacks and compute clusters utilizing ROS/ROS 2, shared-memory IPC, gRPC, sockets, and various serialization formats.
• Incorporate the runtime with Gymnasium-style environment APIs and driving models based on PyTorch.
• Seamlessly integrate execution with both cloud and on-premises environments for closed-loop testing, continuous integration, and perception training purposes.
• Enhance and validate deterministic, bit-accurate, or frame-deterministic execution across simulation, physics, and rendering components.
• Simulate real sensor scheduling and vehicle timing aspects, including camera, rolling shutter, LiDAR, clock drift, latency, transport lag, and packet loss.
• Create perturbation mechanisms to handle timing jitter, dropped or out-of-order frames, and calibration drift.
• Develop memory-efficient multi-world and multi-scenario execution on a single GPU via shared geometry and instancing techniques.
• Optimize GPU memory usage, scene streaming, and scheduling to maximize frames per second per GPU.
• Enhance runtime deployment and asset delivery through deterministic packages, read-only filesystems, memory-mapped storage, and low-overhead loaders.
• Construct distributed caches for textures, shader pipelines, and acceleration structures to minimize cold starts and redundant I/O operations.
• Profile and minimize disk, network, and memory footprints.
• Collaborate with 3D content and USD pipeline teams on runtime budgets, validation rules, and compression workflows.
• Generate technical design documentation, engage in code reviews, conduct reproducibility and performance regression testing, and mentor fellow engineers.
• Bachelor's degree in Computer Science, Computer Engineering, a related technical field, or equivalent practical experience.
• Over 5 years of professional software engineering experience, with a significant focus on performance-critical systems software.
• Expertise in modern C++ (C++17/20), including performance optimization, memory management, and API/system design.
• Proficient in Python for tooling and automation tasks.
• Strong foundation in Linux systems programming, including multithreading, concurrency, memory management, IPC, and high-throughput data movement across processes and machines.
• In-depth knowledge of robotics/autonomous systems or GPU programming using CUDA, OptiX, Vulkan, DXR, or similar APIs, with a willingness to develop skills in the other domain.
• Familiarity with real-time middleware or interfaces such as ROS/ROS 2, DDS, custom IPC, high-rate publish/subscribe, or Gymnasium-style environment APIs.
• Basic understanding of GPU memory and execution models.
• Proven experience in designing, implementing, and debugging reliable distributed systems.
• Background in profiling and optimizing real systems.
• Excellent communication and collaboration capabilities across rendering, simulation, perception, infrastructure, and content pipeline teams.
• Direct experience with autonomous vehicles is not mandatory.
• Relevant experience may be derived from fields such as robotics, perception, simulation, rendering and graphics, game engines, HPC, or distributed systems infrastructure.
• Bonus potential through an incentive pay program based on company performance, job level, and individual performance.
• Medical insurance.
• Dental insurance.
• Vision insurance.
• Health Savings Account.
• Flexible Spending Accounts.
• Retirement savings plan.
• Sickness and accident benefits.
• Life insurance.
• Paid vacation and holidays.
• Tuition assistance programs.
• Employee assistance program.
• GM vehicle discounts.
• Potential relocation benefits for moving to the Bay Area.
• Remote work arrangement.
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