Product Manager, AI/ML & Foundation Models (R4991)

AI Model Development & Training Platform

Own the roadmap for foundation model training workflows, including dataset ingestion, curation, labeling, synthetic data generation, domain model training, and distillation pipelines.

Define requirements for world models, robotics models, and VLA-based training, evaluation, and specialization.

Lead the evolution of MLOps capabilities in Forge, including data lineage, experiment tracking, model versioning, and scalable evaluation suites.

Data, Simulation & Synthetic Data Factory

Define product requirements for synthetic data generation, simulation-integrated data flywheels, and automated scenario generation.

Partner with Digital Twin, Simulation, and autonomy teams to convert natural-language mission inputs into data needs, training procedures, and model variants.

Safe Deployment & Model Governance

Lead the development of model governance and auditability tooling, including model cards, dataset rights, lineage tracking, safety gates, and compliance evidence.

Build guardrails and workflows to safely deploy models onto edge hardware in disconnected, GPS- or comms-denied environments.

Partner with Safety, Certification, Cyber, and Engineering teams to ensure traceability and evaluation pipelines meet operational and accreditation requirements.

Edge Deployment & AI Factory Integration

Partner with Pilot, EdgeOS, and hardware teams to integrate foundation-model-based perception and reasoning into autonomy behaviors.

Define requirements for distillation, quantization, and inference tooling as part of the “three-computer” development and deployment model.

Ensure closed-loop workflows between cloud model training and edge-native execution.

Cross-Functional Leadership

Collaborate with Engineering, Research, Product, Customer Engagement, and Solutions teams to ensure model outputs meet mission and platform constraints.

Translate advanced AI capabilities into intuitive workflows that platform OEMs and partner nations can use to build sovereign AI factories.

Sequence foundational capabilities that unblock autonomy, simulation, and customer-facing product teams.

User & Customer Impact

Develop deep empathy for ML engineers, autonomy developers, and Solutions engineers who rely on the platform.

Capture operational data gaps, mission-driven model needs, and domain-specific specialization requirements.

Lead demos and onboarding for model-development capabilities across internal and external teams.