Senior ML Perception Engineer

Job description

About the role As a Senior ML Perception Engineer at Mytra, you'll be a key member of our Computer Vision team, building the perception stack that gives our distributed robot fleet its situational awareness. This is a hands-on role that spans the full problem: the models that let our robots detect pallet trays and other bots and estimate distance to them, the simulation and data pipelines that produce and validate those models, and the integration that gets perception onto the robot and into the hands of the motion and safety systems. Perception feeds everything downstream: collision avoidance, localization, and safety all depend on how well our robots see and interpret their environment, so this role has real impact across the robotics stack. You'll own significant perception workstreams end to end, from data collection through deployment, and work closely with the camera, robotics, and safety teams. What you’ll do: Build and improve perception models for the fleet, including object detection (pallet trays and bots), depth estimation (using both learned and geometric methods such as projection geometry and calibration), and scene understanding that power collision avoidance and other on-bot behaviors. Own the vision data engine end to end: ETL pipelines that ingest on-bot and rollbot logs, route data through cloud storage and labeling workflows, and produce curated, training-ready datasets on demand, so improvements are measurable and reproducible. Advance simulation and sim-to-real: train and evaluate models in simulation, validate them in software-in-the-loop, and systematically close the gap to real robot data. Develop camera and time-of-flight based localization that feeds the safety system, improving the robustness of fleet localization. Deploy and integrate perception on the robot: optimize models for on-bot compute, publish outputs to downstream consumers, implement consumer handling of perception inputs and build the automated processes to release and monitor models across the fleet. Contribute technical leadership: author design docs, review code, mentor engineers, and help shape the perception roadmap in partnership with the camera/sensing, robotics, and safety teams. Ideal Candidates 5+ years of directly relevant experience building and shipping computer vision or ML perception systems (BS required; MS or PhD preferred). Strong applied computer vision and deep learning skills (detection, segmentation, tracking, depth estimation) together with solid classical and geometric CV, including camera calibration and projection geometry. A track record of shipping perception to production on real systems, with the data-centric debugging instincts to know why models break and how to fix them. Hands-on experience with cameras and depth/ToF sensors, including data collection and calibration. Experience building or operating vision data pipelines and labeling workflows: dataset creation, curation, and assisted or auto-labeling. Strong Python and PyTorch skills, and comfort with C/C++ for on-device or performance-critical code. Simulation and sim-to-real experience (Isaac Sim, Webots, Gym, MuJoCo, or similar). The ability to work across disciplinary boundaries, collaborating with software, controls, and safety engineers to debug real robotic systems. Comfort with ambiguity and an early-stage mindset: you're excited to shape an immature, high-impact area, and you're willing to realize mistakes and pivot. Nice to have: Robotics and systems integration experience (ROS or similar, CAN, pub/sub frameworks) and deploying perception across distributed robot fleets. Edge and embedded model optimization (quantization, pruning, distillation, TensorRT or similar) for resource-constrained on-robot compute. Foundation models, world models, or vision-language approaches applied to perception or simulation. Familiarity with vision data and observability tooling (Foxglove, GCP, Encord, or equivalents). A Final Note: If this role excites you, we encourage you to apply — even if you don’t check every box. At Mytra, we build bots, but we hire humans. We value thoughtful challengers who communicate with clarity and respect, and we’re lifelong learners committed to getting better every day. We move fast, learn faster, and show up for each other under pressure. The best outcomes come from diverse perspectives working together to build something meaningful and built to last Benefits Include: Competitive compensation and equity grants at a high-growth company backed by top-tier VCs Fully subsidized health coverage, including medical (baseline plans), dental, and vision for employees and dependents 401(k) plans and employer-subsidized life insurance Fully subsidized lunch and snacks at HQ—we eat and share stories together at the “long” table Generous PTO and company-paid holidays, including one week over the winter break so everyone can recharge together Voluntary pet insurance, Voluntary Life Insurance, Accident, Critical Illness, and Hospital Indemnity Fully subsidized tax advisory services and education to help you understand your equity Commuter benefits, including a up to $150 monthly commuter benefit Lively, modern combined office and lab space where we rapidly iterate through design, build, and test phases Fully equipped onsite gym and showers at headquarters Pay Notice Compensation for this position will be set based on the candidate's experience level and location. The posted salary band is applicable only to the San Francisco Bay Area and is subject to change. The pay range for this role is: $190,000 – $205,000 About Mytra: We’re creating an entirely new way to solve the most ubiquitous problem in industry - moving and storing material. We’re applying robotics and distributed software to create a new class of product for this $1T market. We’re focused on the supply chain industry first. The industry is in a massive bind with the continued growth of e-commerce, sharp rise in costs, and supply chain disruptions. What has been a “sleepy” industry for decades is now at the epicenter of sustaining the global economy.