Lead AI Dataloop and Release Engineer
Posted Updated
Description
You will define and execute data strategy for model training, simulation, and production deployment. You will own data pipelines, flywheels, training-cluster integration, and simulator data integration. You will establish data quality and traceability standards, lead data and infrastructure engineers, and track pipeline, simulation, and model-readiness metrics.
Responsibilities
- Define and execute data strategy for AI training, simulation, and production deployment
- Own data pipelines from collection and labeling through curation, versioning, and delivery
- Build data flywheels from deployed behavior to future training iterations
- Align data delivery with GPU and TPU training clusters
- Design data pipelines for data-driven, physics-based, and high-fidelity simulators
- Establish regulatory data quality and traceability standards
- Lead, mentor, and grow data and infrastructure engineers
- Define and track pipeline-health, simulation-fidelity, and model-readiness KPIs
Requirements
- Degree in Computer Science, Artificial Intelligence, Data Science, Computer Engineering, Applied Math, or a related subject
- 10+ years of engineering experience
- At least 4 years of technical leadership in data infrastructure, MLOps, or AI platform engineering
- Experience building production data pipelines for AI and ML training
- Experience with dataset management, labeling workflows, and data versioning
- Experience with GPU or TPU clusters, job orchestration, and experiment tracking
- Understanding of simulation pipelines and simulator fidelity
- Experience in safety-critical domains
- Experience building reliable platforms and tooling for engineering teams
Benefits
- Equity grants
- Catered lunches
- Snacks and beverages
- Health insurance
- Dental insurance
- Life insurance
- Unlimited vacation
- 401k matching