Staff Software Engineer, Physical AI
$209,100-$282,900 per year
Apply (opens in a new tab)Staff Software Engineer, Physical AI
Posted 38 days ago
SENIORITY
Lead
SALARY
$209,100-$282,900 per year
About the role
- Platform & systems development
- Build and implement reliable, scalable system services for physical AI workloads.
- Develop runtime infrastructure that enables deployment, lifecycle management, and updates of AI-powered components on-device.
- Develop abstractions that decouple applications from underlying AI frameworks, models, and hardware accelerators.
- Developer experience & tooling
- Build APIs, SDKs, and developer tooling that streamline how engineers build and integrate AI-powered features.
- Improve end-to-end developer workflows, from local development to on-device deployment and updates.
- Build observability and diagnostics capabilities to help developers understand performance, failures, and system behavior.
- Performance, reliability, and scale
- Build software that performs reliably under edge constraints such as limited resources, real-time requirements, and heterogeneous hardware.
- Contribute to system-level performance optimization across CPUs and AI accelerators.
- Ensure systems are maintainable, testable, and robust in production environments.
- Multi-functional collaboration
- Work closely with architects, product managers, and AI engineers to build platform capabilities and developer-facing abstractions.
- Collaborate across teams to build clean APIs, service boundaries, and integration points.
- Contribute to reference implementations, documentation, and example workflows.
- Vital Skills and Experience 6+ years' experience crafting and building systems software, platform services, or distributed systems in production.
- Proficiency in C/C++, Rust, Go, or Python (language choice depends on component).Solid understanding of: Linux-based systems
- Process isolation, IPC, and service lifecyclesAPI build and versioning 3+ years' experience building developer platforms, SDKs, or internal tooling.
- Strong fundamentals in algorithms, data structures, and performance optimization.
- Ability to work across multiple layers of the stack, from APIs down to system behavior.
- Excellent problem-solving, communication, and collaboration skills.
- Experience with container technologies and modern packaging/deployment approaches.
- Familiarity with edge computing, embedded Linux, or real-time systems. Exposure to AI/ML inference systems, even from a platform or infrastructure perspective.
- Experience with heterogeneous computing (CPUs, GPUs, NPUs, DSPs).Background in robotics, vision systems, or physical AI applications.
- Contributions to open-source systems or developer tooling projects.
- Familiarity with security concepts such as secure boot, isolation, or attestation.
- Why this role matters
- Physical AI systems impose outstanding requirements on software platforms. These platforms need to be secure, reliable, updatable, and easy for developers to use. They must also function within real-world limits not found in the cloud.
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
