Physical AI Developer

Physical AI Developers own project areas across robotics simulation, digital twins, ROS 2 infrastructure, robot perception, edge AI, robot datasets, robot-learning benchmarks, world-model experiments, sim-to-real evaluation, research reproducibility, and integrated proof-of-concepts, and are accountable for the Junior and Senior Interns assigned to those areas.

1. Key Responsibilities

- Technical design, architecture and module ownership

- Reusable software development and release management

- Sprint planning, issue assignment and backlog definition

- Task tracking, progress monitoring and blocker resolution

- GitHub issue planning and pull-request review

- Simulation, perception and evaluation pipeline development

- Dataset, benchmark, and model-training workflows

- Edge deployment, model export and latency benchmarking

- Junior and Senior Intern supervision, review and performance reporting

- Upstream open-source contributions

- Research and technical reports

- Release documentation and demonstrations

The role carries a fixed delivery rhythm: weekly sprint planning and issue assignment, midweek technical check-ins and blocker resolution, end-of-week pull-request review, demo and KPI update, and a monthly release, demo day, KPI review and contributor performance review.

A task is complete only when it has a linked GitHub issue, code or technical output, tests, documentation, reproduction instructions, a pull request, review approval, a demo or evidence, and stated known limitations. Physical AI Developers apply this standard to their own work and to every contribution they approve.

2. Requirements

Must-have:

• Robotics or AI engineers, simulation developers, perception engineers, ROS 2 developers, machine-learning engineers, research engineers, and open-source maintainers with delivered project experience. Master’s or PhD holders, and strong final-year candidates with a substantial public delivery history, may also apply.

• Minimum expectations include strong Python, ROS 2, Git/GitHub, independent debugging, technical documentation, testing and reproducibility, code review, task planning, communication, time management, and the ability to direct and unblock less-experienced contributors.

• Your contribution should create verifiable evidence: GitHub history, design documents, reviews, releases, simulations, benchmarks, datasets/models, research experiments, POCs, demonstrations, or technical articles. The same standard applies to the work produced by the contributors you supervise.

• Selected Physical AI Developers must also create an account on Quanverse.ai and may participate in selected workshops, technical sessions, approved article publishing, educational-resource development, university engagement, and Junior and Senior Intern guidance.