Principal Robotics AI Software Lead

Qualcomm Advanced Robotics Team is building an AI stack and platform for next-generation intelligent machines, from AMRs and cobots to emerging humanoids. We pair heterogeneous compute (CPU/GPU/DSP/NPU) with a full Robotics SDK and developer tooling for perception, navigation, manipulation, and fleet workflows. Our mission is to accelerate robotics innovation by leveraging Qualcomm’s leadership in AI, connectivity, and safety architecture.

Role Overview

As Robotics AI Software Lead, you will be the senior technical owner for Qualcomm’s robotics AI software platform. You will define end-to-end architecture, lead cross-functional teams, and deliver production-grade SDKs and reference solutions that customers can deploy at scale. This role combines deep systems expertise with hands-on leadership across AI-driven perception, planning, and control.

Preferred Qualifications

• Strong proficiency in C++ and Python; experience with ROS2/DDS.
• Expertise in robotics AI, including deep learning, reinforcement learning, and motion planning
• Experience with real-time systems, embedded platforms, and heterogeneous compute optimization.
• Familiarity with simulation tools (Gazebo, Isaac Sim) and AI frameworks (PyTorch, TensorFlow).
• Knowledge of functional safety standards and deterministic system design.
  
  
  

Key Responsibilities

• Architecture Ownership: Define and evolve the robotics AI software architecture, including runtime, QoS, and safety envelopes across Linux and MCU subsystems.
• AI Integration: Lead design and implementation of AI-based modules for perception (VIO/VSLAM, semantic scene understanding), planning, and manipulation.
• Performance Optimization: Optimize algorithms for heterogeneous compute platforms (CPU/GPU/DSP/NPU) and ensure real-time performance for robotics workloads.
• SDK Delivery: Ship Qualcomm Robotics SDK with high-quality APIs, samples, and build toolchains; enforce CI/CD and release criteria.
• Validation & Testing: Drive real-world validation using simulation-in-the-loop and hardware-in-the-loop; establish metrics for robustness and determinism.
• Cross-functional Leadership: Collaborate with hardware, AI research, and product teams to align roadmap and deliver integrated solutions.