Key skills
AIMLMLOpsLeadershipCommunication
About this role
Role Overview
- Define and execute a comprehensive data strategy that spans AI model training, simulation, and production deployment across safety-critical autonomous systems
- Own the end-to-end data pipeline ensuring the reliability and scale that training and simulation workflows demand
- Build and maintain data flywheels that continuously improve model performance
- Collaborate closely with teams provisioning and operating large-scale GPU/TPU training clusters
- Drive the design and integration of data pipelines for simulations
- Partner with safety, validation, and certification teams for data quality standards
- Lead, mentor, and grow a team of data and infrastructure engineers
- Define and track KPIs for data pipeline health, simulation fidelity, and model readiness
Requirements
- 10+ years of engineering experience
- at least 4 years in a technical leadership role owning data infrastructure, MLOps, or AI platform engineering at scale
- demonstrated experience building and operating data pipelines for AI/ML model training
- hands-on experience integrating data systems with large-scale distributed training infrastructure (e.g., GPU/TPU clusters)
- deep understanding of simulation pipelines
- experience working in or alongside safety-critical domains
- strong systems-thinking mindset
- track record of building platforms and tooling that other engineering teams depend on day-to-day
- excellent cross-functional communication skills
Benefits
- catered lunches featuring a rotating menu of delicious options
- an assortment of snacks to keep you fueled throughout the day
- a selection of beverages, including coffee, tea, and other drinks, to keep you refreshed
- top-notch benefits package (health, dental, life, unlimited vacation, and 401k with match)
- work/life integration
- support for professional development