Staff Specialist Field Engineer, Autonomous Vehicles

Weights & Biases Weights & Biases · Data AI · Livingston, NJ +1 · Monolith COR

Staff Specialist Field Engineer for Autonomous Vehicles at CoreWeave, focusing on deploying AI solutions in enterprise engineering organizations. The role involves establishing and leading the AV vertical, defining engagement strategies, setting technical standards, and leading customer engagements from initial contact to deployment. Requires deep ML expertise to build, validate, and deploy solutions independently using CoreWeave's AI platform, and translating field observations into product signals.

What you'd actually do

  1. establish and lead this vertical
  2. define how the team engages with autonomous vehicle customers
  3. set the technical standard for the practice
  4. lead complex customer engagements from first contact through to embedded deployment and expansion
  5. build and validate ML solutions independently using our product stack

Skills

Required

  • autonomous vehicle systems development
  • perception engineering
  • motion planning
  • AI/ML for L4-5 autonomous systems
  • autonomous vehicle sensor modalities (camera, LiDAR, radar)
  • ML data characteristics
  • Python
  • modern ML frameworks
  • JupyterHub
  • VS Code
  • Marimo
  • W&B Models
  • ML approaches for autonomous systems (perception, object detection, motion prediction, closed-loop simulation, anomaly detection)
  • ML solution validation
  • leading complex technical customer engagements
  • multi-stakeholder environments
  • executive relationships
  • autonomous vehicle development pipeline
  • closed-loop simulation
  • scenario-based testing
  • data driven approaches to safety case validation
  • translating field observations into product signals

Nice to have

  • functional safety standards (ISO 26262, SOTIF)
  • simulation environments (CARLA, LGSVL)
  • edge deployment of ML models
  • expansion opportunities within strategic customer accounts
  • contributing to internal knowledge frameworks, technical publications, or industry forums
  • AI infrastructure or MLOps environment

What the JD emphasized

  • 8+ years 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 the long-tail distribution and edge case challenges central to L4-5 development
  • Hands-on ML capability: able to build, validate, and deploy ML solutions independently in Python using modern ML frameworks
  • Able to validate ML solutions on engineering grounds and identify when a result is inconsistent with the physical or safety constraints of the domain
  • Able to translate field observations into structured product signals that are actionable for an engineering team

Other signals

  • building and validating ML solutions independently
  • building and iterating on customer-facing applications
  • translate field observations into structured product signals