Senior Machine Learning R&D Engineer

What you'll do

• Research, design, and train large-scale foundational models for 3D reconstruction and generative scene completion.
• Advance state-of-the-art neural rendering techniques such as Gaussian splatting and NeRFs for real-world spaces.
• Develop generative models to fill occlusions, synthesize unobserved viewpoints, and enhance the realism of digital twins.
• Design and optimize scalable training and inference pipelines for large 3D datasets including images, video, and point clouds.
• Translate research prototypes into production-ready systems integrated into the core capture and reconstruction platform.
• Establish rigorous evaluation methodologies and benchmarks to measure reconstruction quality and generative plausibility.
• Contribute to the architectural design and strategic roadmap of the company's foundational reconstruction models.
• Generate intellectual property through patents and publications while representing the company’s work to the research community.

What we're looking for

• Bachelor's degree from an accredited, not-for-profit, in-person university or college.
• Master's or Ph.D. in Computer Science, Machine Learning, Graphics, or a related quantitative field is preferred.
• Proficiency in Python and the PyTorch framework.
• Experience in machine learning R&D with a focus on computer vision, neural rendering, or generative modeling.
• Expertise in large-scale model training infrastructure including distributed/multi-GPU training and data pipeline scaling.
• 5+ years of industry experience in applied ML research and development is preferred.
• Strong track record of publications at top-tier venues or significant open-source contributions.
• Proficiency with data manipulation libraries such as NumPy and Pandas.