Lead AI Dataloop and Release Engineer

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