Member of Technical Staff, RoboticsDepartment: Engineering
Employment Type: Full Time
Location: San Francisco
The RoleThis is a hands-on role with a lot of scope. You'll help set the technical direction of Reactor's robotics work from the ground up. Day to day, you'll get customer models running reliably on our platform under strict latency budgets, wired into real robots.
We're looking for a generalist across ML, systems and robotics. You understand how a policy behaves at inference time, how batching, scheduling and the network path add to its end-to-end latency, and how its output tensor becomes an action in a robot's control loop.
What You'll Do- Serve robot policies (VLAs, IL/RL models) on GPUs under robot-grade latency budgets, and profile the full path from input tensor to output action
- Build the integration layer between Reactor and robot stacks: ROS/ROS2 nodes and bridges, transport, and low-latency channels carrying observations up and actions down
- Use world models for policy evaluation, and tune how we serve rollouts for throughput, fidelity and turnaround time
- Bring teleoperation and human-in-the-loop experience to our real-time transport: synchronization, jitter and failover for a live control loop
- Debug with customer robotics teams across the whole loop: sensor capture, network, inference, action output, robot execution
- Help shape the technical roadmap and set the engineering bar for the team around you
Who You Are- You've run learned policies or ML models on real robots or autonomous systems, and debugged failures from perception through policy, control and hardware
- Strong ML understanding. You know how modern robot policies (VLAs, imitation learning, RL) and world models are built (transformer backbones, action tokenization or diffusion heads, observation encoders) and how they behave at inference time. You won't be training them.
- Depth on inference systems: batching and scheduling, GPU utilization, p99 latency vs. throughput, and running models in real time against physical systems
- Strong C++ and Python in production, and comfortable changing performance-critical code
- Working experience with ROS/ROS2, DDS and robot middleware, from message definitions to transport QoS settings
- Range across ML, systems, cloud infra, networking and robotics. You'd rather fix whatever's blocking the robot than stay in one layer.
- The judgment to lead: setting direction, making tradeoffs explicit and representing Reactor in front of customer engineering teams
Bonus Points- World models, video or diffusion models, or learned simulators for policy evaluation or training
- Teleoperation: low-latency control loops, sensor fusion for human-in-the-loop tools, demonstration data collection
- Inference optimization: INT8/FP8 quantization, CUDA/Triton kernels, TensorRT, vLLM/SGLang-style serving
- Real-time networking: WebRTC, RTP/SRTP, QUIC, jitter buffers, frame budgets
- Infrastructure: multi-tenant GPU serving, autoscaling, data pipelines, eval tooling
- Systems performance: Linux internals, perf/eBPF/GPU profilers, PREEMPT_RT, cgroups, camera pipelines
- Humanoid or dexterous manipulation
- Early-stage startup or founding-engineer experience
LogisticsWe're in person in San Francisco
Benefits- Competitive SF salary and meaningful early equity
- Visa sponsorship and relocation support
- Generous health, dental, and vision coverage
