Principal Engineer - AV Simulation and Evaluation

We are seeking a Principal Software Engineer to architect and build core platform systems to accelerate Physical AI development, such as Autonomous Driving (AV) & Robotics. This is a technical role for someone with expertise at the intersection of data architecture, distributed systems, and Autonomous Vehicle development across cloud, local, and on-road environments. You will own deep technical areas end-to-end: such as AV/Robotics simulation infrastructure and AV performance evaluation. What you will be doing: Design and build simulation and evaluation infrastructure used by AV and ML engineers, to accelerate development of Level 4 self-driving capabilities. Evolve efficient data formats for AV evaluation: designing for performance, interoperability, and correctness across formats like Protobuf, Arrow, Parquet, and MCAP. Collaborate with AI and Robotics teams to deeply understand their simulation and evaluation needs. Build reliable services, APIs, data pipelines, and AV simulation and evaluation workflows and framework that operate at the scale of hundreds of millions of runs per day. Optimize performance at every level: profiling, parallelization, memory efficiency, query optimization, and protocol redesign. Build diagnostic and observability tooling that enables teams to understand and debug their data and test pipelines. Actively drive the adoption of new standards and technologies in the physical AI tooling ecosystem. What We Need to See: BS or MS in Computer Science (or equivalent experience). 15+ years of professional experience in software engineering with focus on distributed systems and data-intensive applications. Proficiency in Go, Python, or Java, and experience operating across the full backend stack. Deep experience building high-performance low-latency data systems: binary serialization, efficient data encoding, columnar data formats. Strong understanding of distributed systems: concurrency, consistency tradeoffs, latency optimization, and compute-efficient design. Ability to identify and fix performance bottlenecks through optimization across the stack, including redesigning protocols and data models. Experience designing and implementing workflows across distributed systems. Past success building foundational systems that multiple teams depend on, with high reliability and scale. Communication skills to be able to translate nuanced system design to both technical and non-technical partners, and talk to users in their language. Ability...

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