Software Engineer, Robotics Simulation & AI Infrastructure

• Design and build core simulator subsystems — scene representation and authoring, physics backends, sensor models, rendering — across the scenarios our robots work in: tabletop manipulation, legged locomotion, navigation and vision, and long-horizon, multi-stage tasks.
• Profile and optimize simulation and training workloads — physics solvers, rendering, data pipelines — so interactive workstation sessions and training throughput at scale stay high.
• Integrate and extend best-in-class open engines — GPU physics, USD/Hydra rendering, offline path tracing — behind clean, swappable interfaces.
• Build high-throughput paths for policy training and synthetic data generation: vectorized environments, GPU-resident state, procedural scene variation, domain randomization, and ground-truth labeling — consistent from an interactive workstation session to scheduled headless runs in the cloud.
• Make simulation a release gate: scenario suites, deterministic replay, benchmarks, and metrics that catch regressions before they reach hardware.
• Enable the continuous learning workflows that simulation feeds into, in partnership with the AI operations team: make simulation a first-class, config-driven stage in collect–merge–train–eval pipelines with reproducible run manifests and artifacts, so the same experiment runs locally and as containerized GPU jobs (Argo Workflows on Kubernetes) without the sim engineer owning the surrounding infrastructure.
• Stand up hardware-in-the-loop configurations: production robotics software running on Qualcomm silicon in communication with the simulator on the host workstation or cloud, and quantify where simulation and reality diverge — system identification, contact and actuator modeling, sensor noise, measured transfer results.
• Partner with AI operations, perception, controls, and silicon teams, and own the design docs, reviews, tests, and APIs others depend on.

• Strong software engineering fundamentals, with production code you can talk through in depth.
• A working grasp of simulation as applied to robotics: rigid-body dynamics, kinematics, coordinate frames, numerical integration, or sensor models. — or the aptitude to build one quickly; engineers from games, graphics, and ML infrastructure backgrounds ramp well here.
• You pick up unfamiliar stacks quickly and independently, and you use modern AI tooling effectively in your development loop.
• You would rather converge two half-parallel code paths than add a third, and you are comfortable where some layers are settled design-of-record and others are still being validated.
• You are motivated by physical AI: work that ends in a robot that functions, not only a benchmark number.

Depth in two or three of these matters more than familiarity with all of them.

If you're excited about this role but don't match every qualification, we encourage you to apply.

• Robotics simulators or real-time 3D engines: MuJoCo/MJX, Isaac Sim or Isaac Lab, Newton, PhysX, Gazebo, Drake, Unreal Engine, or Unity. Candidates from games, VFX, or AV simulation are welcome — these skills transfer directly.
• GPU programming and performance engineering: CUDA, Warp, Vulkan, compute shaders, or accelerator-aware data layout.
• Machine learning for robotics: reinforcement learning at scale, imitation learning, robot foundation models and VLAs, PyTorch.
• 3D graphics and scene pipelines: OpenUSD composition, PBR materials, real-time and offline rendering, sensor simulation.
• Robotics and distributed systems: ROS 2/DDS, URDF/MJCF, pub/sub and schema-driven wire formats, containers, cluster orchestration, and CI/CD for compute-heavy workloads.
• Working fluency in the AI infrastructure around simulation — enough to integrate with it and partner effectively with the AI operations team (who own it), not to run it yourself: Kubernetes-native workflow orchestration (Argo Workflows or similar), containerized GPU jobs and shared-storage datalakes (NFS/PVC volumes), config-driven experiment frameworks, checkpoint/resume semantics, and experiment tracking (TensorBoard, Weights & Biases).
• Effective leverage of modern AI tools as a core engineering skill: frontier AI models, AI coding and agentic workflows, AI-assisted learning for ramping on new domains quickly, and building knowledge bases — personal or team — to accelerate on-boarding and future work.

• Designs, develops, integrates, and validates the in-house simulation platform and its tooling, targeting Qualcomm robotics SoCs and robots across form factors and scenarios — tabletop manipulation, legged locomotion, navigation and vision, and long-horizon multi-stage tasks.
• Specifies environments, tasks, and evaluation criteria for training and assessing robot policies; partners directly with robotics researchers and engineers to iterate on tooling, workflow, and model performance until results hold up on real hardware.
• Builds digital twins of robots, sensors, and work cells, and hardware-in-the-loop configurations where the robotics stack runs on Qualcomm silicon against a simulator on the host, so algorithms are developed and validated before hardware time is committed.
• Builds synthetic data pipelines for robot foundation models and task models, and simulation-based regression suites that gate software releases.
• Works with the in-house sensor teams to model sensor behavior from real characterization and calibration data, delivering high-fidelity sensor simulation modules.
• Works closely with the robotics AI infrastructure team to complete the data flywheel: a continuous learning pipeline spanning data generation, training, evaluation, deployment, and back to data generation.
• Performs code reviews and regression tests; triages and fixes issues; at senior levels, leads design and testing efforts.
• Collaborates with hardware, systems, test, and AI operations teams so simulation integrates with the rest of the program; at senior levels, engages external partners and industry collaborations to advance simulation technology and shape shared roadmaps.
• Writes and reviews technical documentation, design rationale, and knowledge-sharing material for complex software projects.
• At senior levels, articulates technical findings and engineering due diligence — measured capabilities, trade-offs, and honest limits — to leadership, informing roadmap and strategy decisions.

Qualcomm is an equal opportunity employer.

If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process.

You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here .

Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process.

Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities.

We will not respond here to requests for updates on applications or resume inquiries).

To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm.

Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited.

Qualcomm does not accept unsolicited resumes or applications from agencies.

Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location.

Qualcomm is not responsible for any fees related to unsolicited resumes/applications.

EEO Employer: Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.

Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.

Pay range and Other Compensation & Benefits :

The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted.

Even more importantly, please note that salary is only one component of total compensation at Qualcomm.

We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus).

In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play.

Your recruiter will be happy to discuss all that Qualcomm has to offer – and you can review more details about our US benefits at this link .

If you would like more information about this role, please contact Qualcomm Careers .