Staff Specialist Field Engineer, ADAS

The Physical AI Field Engineering team at CoreWeave deploys AI solutions within enterprise engineering organisations, helping customers realise measurable value from machine learning applications. As we build our presence in Advanced Driver Assistance Systems, we are seeking a Staff Specialist Field Engineer to establish and lead this vertical. You will define how the team engages with ADAS customers, set the technical standard for the practice, and lead complex customer engagements from first contact through to embedded deployment and expansion.

This role requires genuine depth on both sides of the engagement: you must be credible to the systems and safety engineers in the room, and capable of building and validating ML solutions independently using our product stack. You will work across CoreWeave’s AI platform (including Monolith, Marimo, and W&B Models) to design and deploy solutions and build customer-facing applications tailored to specific ADAS use cases.

A core part of this role is building and iterating on customer-facing applications using the CoreWeave product stack tailored to specific engineering use cases. These applications are the product the customer uses; you are not just deploying tools but building at the product edge. You will gather and synthesise signals from real customer deployments, identifying where customer needs are consistent enough across accounts to inform development of standalone capabilities. You will contribute to the wider Field Engineering team’s Physical AI knowledge framework and provide critical signals of what customers need in the field and what ultimately gets built in the product.

• 8+ years experience in ADAS systems development, test and validation, perception engineering, or AI/ML for ADAS applications.
• Deep familiarity with ADAS sensor modalities (camera, LiDAR, radar), their data characteristics, and associated ML problem types.
• Hands-on ML capability: able to build, validate, and deploy ML solutions independently in Python using modern ML frameworks.
• Proficient in working directly in JupyterHub, VS Code, Marimo, and W&B Models to build and deploy customer-facing applications.
• Working knowledge of ML approaches relevant to ADAS: anomaly detection, time-series analysis, performance prediction, or sensor data modelling.
• Able to validate ML solutions on engineering grounds and identify when a result is inconsistent with the physical or safety constraints of the domain.
• Proven experience leading complex technical customer engagements, managing multi-stakeholder environments, and maintaining executive relationships.
• Strong understanding of the ADAS development pipeline, including scenario-based testing, HIL/SIL environments, and data-driven validation approaches.
• Able to translate field observations into structured product signals that are actionable for an engineering team.
• Bachelor’s or Master’s degree in Electrical Engineering, Systems Engineering, Computer Science, Physics, or a related technical discipline.

• Knowledge of functional safety standards including ISO 26262 and SOTIF.
• Experience with simulation environments used in ADAS development (CARLA, CarMaker, VIRES VTD, or similar).
• Familiarity with edge deployment of ML models in constrained or safety-critical environments.
• Experience identifying and progressing expansion opportunities within strategic customer accounts.
• Track record of contributing to internal knowledge frameworks, technical publications, or industry forums in the ADAS space.
• Experience working alongside or within an AI infrastructure or MLOps environment.

We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams — even if you aren’t a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk.

• You are equally comfortable discussing perception algorithm design with an ML engineer and sensor validation methodology with a safety engineer, and you know that the most valuable insight often sits at that boundary.
• You want to build AI solutions that are deployed in real engineering environments, not demonstrated in notebooks.
• You find the gap between what ADAS systems can currently validate and what AI-driven approaches could enable to be a genuinely interesting technical problem.
• You want to bring your ADAS domain expertise into a team that already knows how to land and expand AI solutions with engineering customers, and you see being the domain authority that opens a new vertical as a genuinely compelling opportunity.

CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information.

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This position requires access to export controlled information.  To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency.  CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.

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