Staff Specialist Field Engineer

Description:

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.

Who You Are
 

• 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.
   

Preferred
 

• 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.