Staff Specialist Field Engineer, Autonomous Vehicles

CoreWeave•San Francisco, CA

12h•Onsite

About The Position

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 Autonomous Vehicles (L4-5), we are seeking a Staff Specialist Field Engineer to establish and lead this vertical. You will define how the team engages with autonomous vehicle 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 ML engineers, perception researchers and system architects 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 autonomous vehicle 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.

Requirements

8+ years of experience in autonomous vehicle systems development, perception engineering, motion planning, or AI/ML for L4-5 autonomous systems.
Deep familiarity with autonomous vehicle sensor modalities (camera, LiDAR, radar) and their data characteristics, including long-tail distribution and edge case challenges.
Hands-on ML capability: ability to build, validate, and deploy ML solutions independently in Python using modern ML frameworks.
Proficiency in working directly in JupyterHub, VS Code, Marimo, and W&B Models.
Working knowledge of ML approaches relevant to autonomous systems (perception, object detection, motion prediction, closed-loop simulation, anomaly detection).
Ability to validate ML solutions on engineering grounds and identify inconsistencies with physical or safety constraints.
Proven experience leading complex technical customer engagements, managing multi-stakeholder environments, and maintaining executive relationships.
Strong understanding of the autonomous vehicle development pipeline (closed-loop simulation, scenario-based testing, data-driven safety case validation).
Ability to translate field observations into structured, actionable product signals.
Bachelor’s or Master’s degree in Electrical Engineering, Systems Engineering, Computer Science, Physics, or a related technical discipline.

Nice To Haves

Knowledge of functional safety standards including ISO 26262 and SOTIF.
Experience with simulation environments used in autonomous vehicle development (CARLA, LGSVL 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 autonomous vehicles space.
Experience working alongside or within an AI infrastructure or MLOps environment.

Responsibilities

Establish and lead the Autonomous Vehicles vertical for the Physical AI Field Engineering team.
Define team engagement strategies with autonomous vehicle customers.
Set the technical standard for the practice.
Lead complex customer engagements from initial contact through deployment and expansion.
Design and deploy solutions using CoreWeave's AI platform (Monolith, Marimo, W&B Models).
Build and iterate on customer-facing applications tailored to autonomous vehicle use cases.
Gather and synthesize customer feedback from deployments to inform standalone capabilities.
Contribute to the Field Engineering team's Physical AI knowledge framework.
Provide critical signals on customer needs and product development.