Machine Learning - Research

Responsibilities

• Work across the full ML stack (data, model, eval, and infrastructure)
• Implement novel model architectures and training algorithms
• Build data pipelines and training infrastructure for massive, petabyte-scale, multimodal datasets
• Rapidly iterate on experiments and ablations
• Stay up-to-date on research to bring new ideas to work

• Strong grasp of machine learning fundamentals, and depth in at least one core domain (e.g. Computer Vision, Sensor Fusion, Language Models, Physics-informed NNs)
• Experience training models and an ability to understand experiment results through careful analysis and ablation studies.
• Experienced at writing and optimizing massive petabyte-scale data pipelines.
• Familiarity with distributed training and inference.
• [bonus] Familiarity with meteorology, computational fluid dynamics, and/or numerical simulations.

You don’t have to meet every single requirement above.