Principal Engineer, Model Development Platform

About Us Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems. Role Overview As Principal Engineer for the Model Development Platform, you will own the end‑to‑end architecture behind Wayve’s AI model lifecycle, from data ingestion and training to experiment scheduling and on‑road testing. You will partner with the Head of Model Dev Platform to set and execute the technical vision, aligning infrastructure and tooling with company goals. The position requires deep technical expertise across web applications, distributed compute, ML Ops, data pipelines, and optimization algorithms to enable teams to iterate fast and deploy autonomous driving models safely. What You’ll Own System architecture & reliability – design and evolve the platform’s overall architecture for reliability, observability, and scalability; set performance, latency, and availability targets and drive engineering standards to meet them. Cross‑domain technical leadership – unify the platform across disciplines, from front‑end UIs and distributed training to Spark data pipelines and optimization‑based experiment scheduling, ensuring systems interoperate cleanly. Hands‑on problem solving – dive into the hardest challenges across subteams, lead architectural reviews, and propose pragmatic solutions that balance innovation with operational simplicity. Experimentation & scheduling systems – build systems that optimize how models are tested in simulation and on‑road, using techniques such as linear programming and heuristic optimization to balance hardware, safety, and research priorities while improving throughput and turnaround. Data & compute infrastructure – architect pipelines that ingest, transform, and enrich petabytes of fleet sensor data, and drive efficient compute use across GPU, CPU, cloud, and edge for both prototyping and large‑scale training. Strategic collaboration – partner with Product, Research, and Operations to align architecture with user needs and co‑own the platform’s long‑term roadmap. About You Essential Technical Leadership at Scale – 10+ years of experience designing and building large‑scale distributed systems, ML/AI infrastructure, full‑stack web application, or developer platforms, including at least 3 years as a staff or principal‑level engineer. Architectural Depth & Breadth – proven ability to design systems spanning web platforms, ML pipelines, and large‑scale compute orchestration (e.g., Spark, Ray, Kubernetes, Airflow, MLflow). Reliability and performance – experience driving platform reliability improvements, defining SLAs/SLOs, and building self‑healing and observable systems that operate at four nines availability or better. Hands‑On Systems Design – deep understanding of distributed computing, workflow orchestration, data modeling, and API design, with the ability to write and review production‑quality code. Collaborative Influence – excellent communication and cross‑functional collaboration skills; ability to guide engineers, managers, and researchers toward unified technical direction. Mentorship & Culture – demonstrated success in mentoring engineers across levels and cultivating a culture of engineering excellence. Desirable Optimization & Scheduling Expertise – experience applying algorithmic or mathematical optimization (e.g., linear programming, graph algorithms) to operational or scheduling problems. ML Ops & Experimentation Systems – familiarity with end‑to‑end model lifecycle tooling, from data ingestion and training CI to model artifact tracking and evaluation workflows. Domain Experience – prior exposure to autonomous systems, robotics, or other safety‑critical domains. Full‑Stack Fluency – experience with modern web frameworks (e.g., React, Flask, FastAPI) and how they integrate into backend systems. Data Governance – understanding of data privacy, compliance, and secure handling practices for large‑scale sensor data. This full‑time role is based in Sunnyvale, CA (hybrid). The estimated salary range is $295,500 to $335,300, plus a competitive equity package. Compensation is based on the candidate’s skills, qualifications, and experience. Wayve is committed to creating an inclusive interview experience. If you require any accommodations or adjustments to participate fully in our interview process, please let us know. We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self‑driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply. At Wayve we’re committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law. DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non‑discriminatory. #J-18808-Ljbffr Wayve