Top Tech Jobs & Startup Jobs

Own software serviceability for humanoid robots: design and validate diagnostics, firmware/bootloader recovery, remote-diagnostics content, tooling for fast fault localization, and act as Services interface to R&D. Validate OTA, calibration, and repair procedures and support new service introductions.

Lead employer branding to attract technical talent by building community relationships, running events (hackathons, meetups, university partnerships), creating content with PR & Marketing, improving careers site and employee advocacy, and measuring impact to continuously optimize talent attraction.

Lead ownership of ML models and infrastructure lifecycle: develop, deploy, monitor, and improve ML systems. Build CI/CD for software and ML workflows, automate orchestration and environment management, ensure scalability, reliability, observability, and security, troubleshoot production issues, and document operational procedures while collaborating with engineers, data scientists, and product teams.

Lead design, build, and commission in-house test rigs and fixtures for humanoid robot subsystems and full robots. Define validation scope with system owners, specify and source test equipment, manage vendors and budgets, implement mechanical and electrical designs, and support long-term reliability, certification, and data acquisition for validation programs.

Develop and deploy robot manipulation capabilities by training and fine-tuning policies (behavior cloning and RL), curating and preprocessing datasets, iterating simulation/digital twin training, expanding observation/action spaces, partnering with teleoperation, controls and hardware teams to ensure smooth transfer and improve real-world performance.

Lead and own the Services Business Process Automation program including SLM platform, BI reporting, and IT/OT integrations. Define roadmap, manage cross-functional deployments end-to-end, govern risks and budgets, measure adoption and SLAs, manage vendors, and translate technical work into executive narratives.

Lead design and delivery of end-to-end learned navigation and behavior systems for humanoid robots, build VLA/VLM-based multimodal navigation, design data pipelines and evaluation frameworks, and productionize large-scale ML models for reliable deployment on physical hardware in dynamic, multi-agent environments.

Develop and own core embedded OS, networking, and software subsystems for humanoid robots. Integrate sensors and computing platforms, write high-integrity Linux-based code, lead cross-functional projects, validate systems for safety and reliability, and build infrastructure for rapid R&D iteration.

Execute end-to-end software release validation and regression testing on physical humanoid robots and in simulation. Design and run policy evaluations, compare sim-to-real behavior, collect reliability and performance metrics, maintain CI/CD test suites and dashboards, and ensure test data quality to determine release readiness.

Lead design and implementation of SLAM, state estimation, long-term mapping, and localization systems for humanoid robots. Integrate modern ML and foundation geometry models into navigation pipelines, build auto-labeling data workflows, deploy and benchmark spatial AI on edge hardware, and bridge research to production for robust, low-latency robot navigation in dynamic real-world environments.