Staff ML Engineer Gaia

Job description

Job responsibilities

• Lead and execute large-scale training runs for video (or adjacent) foundation models, from experimental design through production-grade execution
• Contribute to model architecture and training strategy, using first-principles understanding rather than “off-the-shelf” application
• Improve world-model capabilities that enable synthetic scenario generation and downstream evaluation/training of the driving model
• Partner closely with research, applications, simulation engineering, and cloud/infrastructure teams to deliver end-to-end impact
• Provide technical leadership through mentorship, review, and setting high engineering/research standards (Senior/Staff scope)

Job requirements

• In-depth experience training large-scale models (language, video, or other foundation models), including ownership of training at scale
• Strong understanding of model architecture and the ability to contribute meaningfully to architectural/training decisions
• Strong hands-on engineering skills with modern ML stacks (e.g., PyTorch), including debugging and performance/reliability-minded development
• Relevant industry experience (typically 4–5+ years); advanced degrees are valued, but depth of applied experience is important
• Direct experience with world models, video generation, or long-horizon prediction
• Experience improving data/training pipelines and working across infrastructure constraints (distributed training, efficiency, reliability)
• Proven technical leadership (tech lead ownership, mentoring, setting direction across an area)