Design and build the autonomy stack for a rugged humanoid platform, integrating perception, manipulation, navigation, and safety to enable complex industrial tasks.
Build and own core parts of the teleoperation system that lets a person step inside a humanoid robot and work through it in real time, from the operator’s headset to the robot and from simulation through deployment at customer sites.
Compensation
We offer competitive compensation, a performance-based bonus, 100% employer covered medical benefits for most healthcare plans, early-stage equity, competitive PTO, and company-wide paid winter break between December 24th and January 2nd.
Responsibilities
Design and build the headset application and robot‑side services, written primarily in Rust
Build the native OpenXR application operators use to drive humanoids, robot arms, and dexterous hands, including its HUD, onboarding, and in‑headset guidance
Stream stereo video and robot state to the operator, and operator commands to the robot, with low latency over Wi‑Fi and wide‑area networks, and keep the robot safe when the connection degrades
Map operator motion onto the robot, including whole‑body and arm retargeting, dexterous hand retargeting, and pre‑programmed grasps
Work with locomotion, controls, autonomy, and machine learning engineers so teleoperation produces high‑quality training data and can take over when autonomy needs help
Design and implement advanced robot learning models and training procedures to achieve dexterous manipulation for humanoid robots with high DOF and multi‑fingered hands.
Own the ML manipulation pipeline and roadmap, combining different learning paradigms to achieve real‑world, industrial‑level robustness.
Work with the Teleoperation and Data team to design data collection, sensor modularity, and data mixture strategies.
Leverage existing state‑of‑the‑art manipulation models and contribute to the development of new architectures for emerging complex tasks.
Deploy trained manipulation models to robotic hardware, ensuring real‑time performance, safety, and integration with control systems and sensors.
Machine Learning Engineer to drive Persona’s large-scale ML infrastructure and facilitate the robot learning effort.
Compensation
We offer competitive compensation, a performance-based bonus, 100% employer covered medical benefits for most healthcare plans, early-stage equity, competitive PTO, and company-wide paid winter break between December 24th and January 2nd.
Responsibilities
Contribute to Persona’s large-scale ML software stack across data, training, and evaluation.
Design and implement the ML software infrastructure with thoughtful abstraction and scalability.
Work with the ML team to craft and execute a comprehensive plan for the development of machine learning models.
Develop comprehensive test suites to ensure correct and performant execution of the ML pipelines.
Leverage cloud platforms for flexible compute capacity, data management, and task automation.
Help turn a sophisticated optical sensing system into a high-performance wearable for understanding the brain. You'll shape how your wearable acquires, processes, and delivers neural measurements.
Responsibilities
Develop the C++ software that controls acquisition, configures peripherals, runs self-tests, and manages recording sessions.
Design and optimize the path from raw sensor frames through on-device signal processing to a timestamped network stream.
Evolve our Yocto-based Linux platform, including application integration, system configuration, and reproducible builds.
Solve timing, concurrency, memory, and throughput challenges across a high-performance wearable.
Collaborate with hardware and FPGA engineers to bring new sensing capabilities to life.
Senior Robotics Software Engineer, AutonomyNewPersona AI Inc · Houston, US
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