Sunday
Robotics
SystemSoftwareEngineer,RobotPlatform—GPU&AcceleratedCompute
Neural analysis suggests this role is
optimal for Mid candidates.
“System Software Engineer, Robot Platform — GPU & Accelerated Compute at Sunday. Skills: GPU systems software, CUDA, C++, C, Rust, GPU architecture, GPU scheduling, CPU/GPU data transfer, CPU/GPU synchronization. Own and contribute to the accelerated compute layer of the robot platform. Efficient model execution and switching”
What You'll Achieve.
Ensure the GPU is a first-class, well-utilized resource that meets the latency and throughput requirements of a real-time robotic system operating in the home; Reduce gpu kernel launch overheads; Make swapping between models on the same device fast and predictable; Arbitrate GPU access across concurrent users with predictable latency; Drive low-latency transfer of camera frames into GPU memory; Build efficient, low-overhead data movement between host and device; Design synchronization primitives and patterns that minimize stalls and keep inference pipelines full
Industry & Context.
What They're Looking For.
Must Have
2+ years of experience developing gpu systems software, proficiency in CUDA, proficiency in a systems language such as C++, C, or Rust, Solid understanding of GPU architecture, Solid understanding of GPU workloads, Solid understanding of the tradeoffs involved in time-slicing and sharing the device across users, Hands-on experience with the CUDA ecosystem: CUDA runtime API, CUDA Graphs, and CUDA IPC, Solid Linux fundamentals: scheduling, IPC, memory management, and performance tuning
Nice to Have
Contributions to CUDA libraries or other GPU programming libraries, Experience with camera pipeline integration and NVDEC/NVENC, Experience optimizing model inference on embedded GPU platforms (e. g. , Jetson), Experience with observability and tracing for GPU-accelerated workloads
What You'll Do.
Own and contribute to the accelerated compute layer of the robot platform
Efficient model execution and switching
GPU scheduling and time-slicing
Camera pipeline development
CPU ↔ GPU data transfer optimization
CPU/GPU synchronization design
How You'll Work.
Team & Collaboration
Work alongside teammates who own the runtime and our build and delivery infrastructure; Partner cross-functionally with ML, SLAM/Perception, Controls and Hardware teams
Full Job Description
Join Us in Building the Future of Home Robotics At Sunday, we're developing personal robots to reclaim the hours lost to repetitive tasks. We're focused on an ambitious goal to make generalized robots broadly accessible, enabling households to take back quality time. We have spent the last 18 months building a talented team, securing capital, and validating our technology. We are now seeking passionate individuals to join us in the next phase of our growth. If you are ready to apply your skills to the forefront of robotics innovation, we’d love to hear from you. What to Expect The Robot Platform team builds the foundational systems that every part of our robot perception, ML, controls and behavior runs on, and the developer infrastructure that lets us build, ship, and update that software quickly and safely on every robot in the fleet. As a System Software Engineer on Robot Platform focused on GPU and accelerated compute, you’ll own how every accelerated workload on the robot from model inference, SLAM/perception, and more gets data, gets scheduled and runs efficiently on shared compute. You’ll work alongside teammates who own the runtime and our build and delivery infrastructure, and you’ll partner cross-functionally with ML, SLAM/Perception, Controls and Hardware teams to ensure the GPU is a first-class, well-utilized resource that meets the latency and throughput requirements of a real-time robotic system operating in the home. What You’ll Do You’ll own and contribute to the accelerated compute layer of the robot platform, including: - Efficient model execution and switching: Reduce gpu kernel launch overheads and make swapping between models on the same device fast and predictable - GPU scheduling and time-slicing: Arbitrate GPU access across concurrent users (model inference, SLAM, and other robotics applications) with predictable latency - Camera pipeline: Drive low-latency transfer of camera frames into GPU memory, integrating with HW accelerate encode/decode
Applying for this System Software Engineer, Robot Platform — GPU & Accelerated Compute role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on Ashby
- Ashby is a fast modern ATS — most applications take under 3 minutes.
- The resume parser is strong; verify parsed experience dates and job titles.
- Custom screening questions are often scored algorithmically — answer completely.
- Location field affects geo-based screening; use your actual metro area.
ANONYMOUS · UNFILTERED
What do employees actually say about Sunday?
Real rants from real employees. Read before you apply.