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Open nowPosted 152 days ago

Software Engineer, Verification & Validation

FieldAI95 open roles

Pay
$135,000 – $190,000 a year
Where
Irvine, CA
Work mode
On site
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Your applicationOpen nowSoftware Engineer, Verification & ValidationFieldAI · Irvine, CA

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This job: posted 152 days ago

The posting

Field AI is transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications.

Learn more at https://fieldai.com.

What You'll Get to Do

1. Own End-to-End Robot Verification & Validation

  • Design and execute verification and validation strategies for complete robotic systems, from individual capabilities through full autonomous missions
  • Develop clear acceptance criteria, performance metrics, and test methodologies for new robot capabilities
  • Validate system behavior across multiple robotic platforms, environments, and operating conditions
  • Build repeatable qualification and regression processes that allow new capabilities to ship without compromising existing functionality
  • Establish a clear understanding of what “deployment-ready” means and provide quantitative evidence that systems meet that bar.

2. Build Scalable Robotics Test Infrastructure

  • Develop automated test infrastructure spanning simulation, hardware-in-the-loop, lab testing, and full robot operation
  • Create reusable test scenarios and evaluation frameworks that exercise autonomy under nominal, edge-case, and failure conditions
  • Build tools for experiment execution, telemetry collection, automated analysis, visualization, and reporting
  • Improve the reproducibility of robot testing so failures can be recreated, diagnosed, and verified efficiently
  • Help move validation from individual one-off tests toward continuously running, scalable system evaluation

3. Validate Real-World Robot Behavior

  • Design tests that expose robots to the uncertainty and variability encountered in real deployments
  • Exercise systems across changing terrain, obstacles, environmental conditions, sensor degradation, communication failures, compute limitations, and other realistic disturbances
  • Evaluate not only whether a robot succeeds, but how reliably, safely, and consistently it behaves across repeated trials
  • Identify performance boundaries and characterize where system behavior begins to degrade
  • Work directly with physical robots in the lab and field to reproduce difficult system-level failures

4. Turn Failures Into Engineering Signal

  • Debug failures across autonomy, sensing, state estimation, planning, control, system integration, compute, networking, and hardware boundaries
  • Use telemetry and experimental data to isolate root causes rather than simply identify symptoms
  • Develop tooling and instrumentation that make complex robot behavior easier to understand
  • Convert field failures and difficult-to-reproduce issues into deterministic regression tests whenever possible
  • Partner with subsystem owners to verify fixes and prevent recurrence

5. Drive System Reliability and Release Readiness

  • Partner closely with autonomy, robotics software, hardware, systems, and field teams throughout the development lifecycle
  • Identify integration and reliability risks early and ensure they are represented in the validation process
  • Build dashboards, scorecards, and automated evaluations that provide a clear view of system health and capability maturity
  • Help define release gates based on measurable system performance rather than subjective readiness
  • Continuously improve the V&V process as the autonomy stack, robot platforms, and deployment environments evolve

What You Have

  • Bachelor’s, Master’s, or PhD degree in Robotics, Computer Science, Electrical Engineering, Mechanical Engineering, or a related technical field, or equivalent hands-on industry experience
  • Strong software engineering fundamentals with proficiency in C, C++, and Python for developing, integrating, debugging, and testing robotic systems
  • Hands-on experience developing, integrating, testing, or debugging physical robotic or autonomous systems
  • Broad understanding of robotic systems, including sensing, state estimation, planning, control, communication, compute, and actuation
  • Experience developing and debugging robotics software using ROS 2 and distributed message-passing architectures
  • Strong experience working in Linux environments, with familiarity with real-time systems and RT-patched Linux kernels
  • Proficiency with Git and modern collaborative software development practices, including code review, branching, integration, and regression workflows
  • Experience diagnosing complex system-level failures where root causes may span software, middleware, networking, compute, sensors, and hardware
  • Experience designing quantitative experiments, defining performance metrics, and analyzing robot telemetry and test data to evaluate system behavior and reliability
  • Strong instincts for testability, observability, reproducibility, and systematic debugging, with the ability to turn ambiguous robot behavior into concrete hypotheses, experiments, and actionable engineering work
  • Experience developing system-level V&V, qualification, or release processes for autonomous robots, vehicles, drones, or other complex physical systems
  • Experience building automated regression testing or large-scale evaluation infrastructure for robotics.
  • Familiarity with simulation, hardware-in-the-loop, fault injection, or scenario-based testing
  • Experience defining reliability metrics, operational performance envelopes, or quantitative release criteria
  • Experience with automated telemetry analysis, experiment management, or fleet-level performance evaluation
  • Experience testing robotic systems in unstructured, dynamic, or safety-critical environments
  • Experience bringing new robotic capabilities from initial integration through production deployment
  • A track record of finding subtle system-level problems that were difficult to reproduce or crossed traditional subsystem boundaries
  • The ability and willingness to get hands-on with robots, understand the complete system, and go wherever the problem leads
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