Senior Machine Learning Engineer - Physical AI and Synthetic Data Generation

What you'll do

• Develop and implement advanced generative pipelines for high-fidelity synthetic data in Physical AI applications.
• Build and fine-tune large-scale multimodal models using transformer and diffusion-based architectures.
• Apply user controls to ensure precise environmental control during data generation.
• Establish KPI evaluation processes to validate the quality of synthetic datasets.
• Create automated QA pipelines using classical computer vision algorithms and VLMs.
• Lead the generation of massive training datasets with state-of-the-art tools and techniques.
• Optimize ML software performance, test, and document throughout its lifecycle.

What we're looking for

• BS, MS, or PhD in Computer Science, Robotics, or related field with 12+ years ML experience.
• Expertise in image/video synthesis using diffusion models and multimodal methods.
• Proficiency in Python and major DNN libraries for large-scale training datasets.
• Strong analytical skills to validate synthetic data quality and physical accuracy.
• Experience in optimizing code efficiency and workflow management for high performance.
• Collaborative team player with excellent communication skills in a tight-knit environment.