Battery Algorithm Engineer (Robotics)
About The Position
About 1X We’re an AI and robotics company based in Palo Alto, California, on a mission to build a truly abundant society through general-purpose robots capable of performing any kind of work autonomously. We believe that to truly understand the world and grow in intelligence, humanoid robots must live and learn alongside us. That’s why we’re focused on developing friendly home robots designed to integrate seamlessly into everyday life. We’re looking for curious, driven, and passionate people who want to help shape the future of robotics and AI. If this mission excites you, we’d be thrilled to hear from you and explore how you might contribute to our journey. Role Overview You will develop real-time battery estimation, control, and optimization algorithms that directly impact robot autonomy, uptime, safety, and user experience. This role sits at the intersection of robotics, embedded systems, control theory, and electrochemistry.
Requirements
- Education: MS/PhD in Electrical Engineering, Control Systems, Robotics, Applied Mathematics, or related field (BS with strong experience considered).
- Experience: 3+ years developing estimation, control, or battery algorithms for robotics, automotive, aerospace, or other safety-critical systems.
- Strong foundation in estimation theory, control systems, and numerical optimization.
- Hands-on experience with lithium-ion batteries and Battery Management Systems.
- Proficiency in Python and/or MATLAB for algorithm development and analysis.
- Experience implementing algorithms in C/C++ for embedded or real-time systems.
Responsibilities
- Develop and deploy real-time battery state estimation algorithms for robotic platforms, including SoC, SoH, SoP, and remaining runtime under dynamic loads.
- Design robust observers and filters (EKF/UKF/Particle Filters) that operate reliably under highly transient robotic duty cycles.
- Build physics-based, data-driven, or hybrid battery models tailored to robotics use cases (high C-rates, intermittent loads, regenerative events).
- Develop degradation-aware charging and power-limiting strategies to maximize battery lifetime while preserving robot performance.
- Collaborate closely with robotics controls, autonomy, hardware, and firmware teams to integrate algorithms into the robot BMS and runtime stack.
- Define safety margins, diagnostics, and fallback strategies for battery-related failures.
- Analyze fleet data to continuously improve estimation accuracy, robustness, and safety.
- Contribute to system-level energy management strategies across perception, control, and actuation.
Benefits
- Health, dental, and vision insurance
- 401(k) with company match
- Paid time off and holidays
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
