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Robotics Software Test Engineer

Rhoda ai
Posted a month ago, valid for 21 days
Location

Palo Alto, Santa Clara 94301, CA

Salary

Competitive

Contract type

Full Time

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Sonic Summary

info
  • Rhoda AI is seeking a Robotics Test / QA Engineer to develop test infrastructure for their humanoid robot software stack.
  • Candidates should have proficiency in Python and C++, along with experience in designing test infrastructure and CI/CD systems.
  • The role requires strong debugging skills and a solid understanding of software testing methodologies, with a self-starter mentality.
  • The position offers a salary of $120,000 per year and requires at least 3 years of relevant experience.
  • This role is crucial in ensuring software reliability and quality before deployment in real-world applications.

At Rhoda AI, we're building the full-stack foundation for the next generation of humanoid robots — from high-performance, software-defined hardware to the foundational models and video world models that control it. Our robots are designed to be generalists capable of operating in complex, real-world environments and handling scenarios unseen in training. We work at the intersection of large-scale learning, robotics, and systems, with a research team that includes researchers from Stanford, Berkeley, Harvard, and beyond. We're not building a feature; we're building a new computing platform for physical work — and with over $400M raised, we're investing aggressively in the R&D, hardware development, and manufacturing scale-up to make that a reality.

We're looking for a Robotics Software Test Engineer to design and build the test infrastructure that ensures our robot software stack is reliable, regression-free, and ready to ship.

What You'll Do

  • Design and implement automated test plans, test cases, and test fixtures across the full robotic software stack

  • Architect and build test infrastructure across all testing layers — spanning unit tests, component integration tests, system-level tests, and hardware-in-the-loop validation

  • Strengthen and extend CI/CD pipelines to catch regressions early and gate releases

  • Define quality metrics and KPIs; track test coverage, failure trends, and release readiness to give the team clear signal on product health

  • Investigate and root-cause production failures; drive corrective actions and build regression tests to prevent recurrence

  • Participate in design and code reviews with a focus on observability, testability, and reliability

What We're Looking For

  • Proficiency in Python and C++

  • Strong knowledge of software engineering best practices and design patterns

  • Experience designing and building test infrastructure

  • Hands-on experience with CI/CD systems

  • Strong debugging and root-cause analysis skills — able to investigate failures across software, hardware, and system boundaries

  • Solid understanding of software testing methodologies across multiple layers

  • Experience with Linux-based development and production environments

  • Self-starter mentality — comfortable with ambiguity, able to prioritize independently, and willing to jump in wherever needed

  • Effective communication skills; able to work cross-functionally in a small, fast-moving team

Nice to Have (But Not Required)

  • Experience with Docker and containerized environments

  • Experience with Bazel or similar build systems

  • Familiarity with perception systems

  • Knowledge of industrial communication protocols (EtherCAT, Modbus, gRPC, etc.)

  • Understanding of networking fundamentals (TCP/IP, DNS, firewalls) and security best practices for embedded IoT devices

  • Experience contributing to product design processes

Why This Role

  • Own the quality bar for a humanoid robot software stack — your test infrastructure is the last line of defense before code runs on real hardware in the real world

  • Build foundational QA systems from the ground up at a critical moment in the company's development, with direct influence over how the engineering team ships

  • Work at the intersection of software reliability and physical robotics, where a missed regression isn't just a bug — it has consequences in the physical world




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