Lead Robotics Software Engineer - Dexterous Manipulation

Apptronik; Mountain View (CA); On-site; USD 150,000 - 190,000; Full time

Job summary

Apptronik in Austin, Texas, seeks a Lead Software Engineer - Dexterous Manipulation to drive learning-based hand control software and bridge research to production.

You will own architectural frameworks, pursue sim-to-real strategies, and mentor teams while delivering robust C++/Python code for high-DOF robotic hands.

This senior role shapes hardware interaction, sensing, and control policies across the Apollo platform to achieve safe, reliable manipulation in real-world settings.

Qualifications

• Deep expertise in multi-fingered hand control and in-hand manipulation.
• Proficiency in learning-based control for robotics (e.g. RL, imitation learning).
• Experience building real-time robotic software stacks in Python/C++.
• Experience with physics engines for policy training (IsaacSim, MuJoCo, Drake).

Responsibilities

• Strategic Ownership: technical authority for dexterous manipulation; create long-term roadmap.
• Architectural Definition: design foundational software frameworks for manipulation; balance autonomy with teleoperation.
• Research & Innovation: integrate state-of-the-art policies and vision systems.
• Sim-to-Real Ownership: set standards for virtual environments to optimize policy transfer to hardware.
• Hardware Design Influence: drive requirements for sensing, DOF, and torque profiles.
• Production Excellence: ensure reliability of production-level code on fleet hardware.
• Technical Leadership & Culture: foster technical rigor and mentor future robotics leaders.

Skills

Dexterous Manipulation

Advanced Control & Learning

Software Engineering

Simulation Environments

Education

BS/MS/PhD in Robotics, CS, EE

Tools

Python

Job description

Apptronik in Austin, Texas, seeks a Lead Software Engineer - Dexterous Manipulation to drive learning-based hand control software and bridge research to production.

You will own architectural frameworks, pursue sim-to-real strategies, and mentor teams while delivering robust C++/Python code for high-DOF robotic hands.

This senior role shapes hardware interaction, sensing, and control policies across the Apollo platform to achieve safe, reliable manipulation in real-world settings.