Principal Data Scientist

What's the role? We are hiring a Principal Data Scientist to lead advanced generative AI and computer vision work across simulation-grounded visual systems, structured-control generation, and production-oriented AI products. This person will help define and build model capabilities that sit at the intersection of generative modeling, scene understanding, controllability, and applied computer vision. This is a senior technical role for someone who can move from early research ambiguity to production-quality model systems while maintaining a high bar for technical depth, rigor, and practical value. This role is intended for someone who can own a major technical pillar, set direction for that domain, and raise the standard for how advanced AI systems are built and shipped. What You Will Own - Own the model strategy and technical direction for advanced generative and multimodal vision systems - Set the research and engineering agenda for model adaptation, evaluation, and production readiness within this domain - Define how model inputs, controls, outputs, and interfaces are represented and integrated into downstream systems - Improve realism, controllability, temporal consistency, robustness, and deployment readiness over time - Work closely with evaluation, simulation, and platform engineers to define durable interfaces between research systems and production workflows - Drive model benchmarking, ablation studies, model-selection decisions, and the path from pre-trained baselines to production-ready capability - Raise the bar for technical quality, architecture, and execution within the model stack What You Will Do - Build and evolve end-to-end model workflows for complex vision and generative AI systems - Identify and reduce failure modes such as structural drift, temporal instability, inconsistent outputs, and production fragility - Define the fine-tuning, adaptation, or hybrid-model strategy when pre-trained models do not meet product requirements out of the box - Partner with the evaluation lead to establish quality metrics, release gates, and production-readiness criteria - Help shape the roadmap from initial prototypes to scalable AI capabilities across perception, generation, and related vision tasks - Contribute to deployment decisions around model packaging, inference optimization, and production performance tradeoffs - Mentor other scientists and act as the senior technical owner for the model domain What We Are Looking For: - Deep experience in generative modeling for video, world models, diffusion models, multimodal systems, or adjacent advanced vision domains - Evidence of principal-level scope through technical leadership, research impact, architectural ownership, or shipped systems - Strong background in PyTorch and modern model training, fine-tuning, evaluation, and inference workflows - Experience adapting large pre-trained models to domain-specific use cases and hard production constraints - Good judgment on model quality, controllability, reliability, and deployment tradeoffs - Ability to work across research and engineering boundaries in a small, hands-on team Education & Experience - Master’s or PhD in Computer Science, AI, Machine Learning, or related field. - 10+ years of experience in deep learning, computer vision, or multimodal AI. Nice To Have - Experience with synthetic data, robotics, perception systems, geospatial AI, autonomous systems, or advanced mapping products - Familiarity with conditioning mechanisms, structured control inputs, simulation-grounded models, or controllable generation - Experience running large-model inference, optimization, or fine-tuning on AWS GPU infrastructure - Experience taking research models into production environments