Lead Software Engineer - Dexterous Manipulation

Apptronik
Sunnyvale, Mountain View, Austin
Workplace: OnsiteFull timeFunction: Software EngineeringExperience: 5+ yearsSkills: ["Technical leadership","Technical rigor","Mentorship","Cross-functional influence"]

Lead the development of learning-based dexterous manipulation for a humanoid robot, bridging cutting-edge research to production-ready software. Own the long-term technical roadmap and define scalable manipulation software architecture that balances autonomous control with high-fidelity teleoperation. Integrate state-of-the-art learning policies, drive sim-to-real standards using physics simulation tools, and influence next-generation hardware requirements to enable reliable, fleet-wide performance.

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Apptronik
Apptronik
1 day ago

Lead Software Engineer - Dexterous Manipulation

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Last checked: 6 hours agoStatus: Live

Job Summary

Lead the development of learning-based dexterous manipulation for a humanoid robot, bridging cutting-edge research to production-ready software. Own the long-term technical roadmap and define scalable manipulation software architecture that balances autonomous control with high-fidelity teleoperation. Integrate state-of-the-art learning policies, drive sim-to-real standards using physics simulation tools, and influence next-generation hardware requirements to enable reliable, fleet-wide performance.
Location: Sunnyvale, Mountain View, Austin
Workplace: Onsite
Employment Type: Full time
Job Function: Software Engineering
Seniority: Mid level

Key Responsibilities

  • •Serve as the technical authority for dexterous manipulation, creating the long-term technical roadmap for multi-fingered hand control.
  • •Design and enforce foundational manipulation software frameworks, balancing autonomous logic with high-fidelity teleoperation for scalability to future hardware.
  • •Integrate state-of-the-art research by selecting and deploying learning-based policies and vision-integrated systems defining physical capabilities.
  • •Lead sim-to-real strategy by setting high-fidelity simulation standards to optimize policy transitions to physical fleet hardware.
  • •Oversee production excellence by transitioning from experimental research to fleet-wide deployment, ensuring reliability of C++/Python code on production assets.

Key Requirements

  • •Deep expertise in multi-fingered hand control, grasp planning, and in-hand manipulation with proven hardware deployment.
  • •Proficiency in learning-based control for robotics, including reinforcement learning and reward modeling, with strong vision-to-action capability.
  • •Proficiency in Python and experience building real-time robotic software stacks for production use.
  • •Experience training and validating policies in simulation environments using physics engines such as IsaacSim, MuJoCo, or Drake.
  • •A BS/MS/PhD in Robotics, Computer Science, Electrical Engineering, or related field, plus 5+ years of relevant experience (or 3+ with a PhD) deploying algorithms from research to hardware.
Experience:5+ yearsRoboticsHuman-centered AIComputer visionReinforcement learningRobot manipulationSimulation-to-real
Education:
Skills:Technical leadershipTechnical rigorMentorshipCross-functional influence
Languages:English
Tech Stack:PythonC++IsaacSimMuJoCoDrakeReinforcement learningImitation learningTeleoperationVRHaptic interfaces6D pose estimationPoint cloud processingVisual servoing

Company Brief

Apptronik
Develops advanced general-purpose robots and robotic limbs for industrial and commercial applications, combining hardware, actuators, and control software to enable versatile, human-scale robot solutions.
Industry: Robotics
Company Size: Medium (51 to 250 employees)
Growth: Growth Stage Startup
Funding: Series A
Headquarters: Austin, United States
Founded: 2018
WebsiteLinkedIn