Develop innovative ML models: Design and implement video-to-video diffusion models and efficient 4D feed-forward reconstruction methods.
Improve scalability and performance: Optimize models and pipelines to support large-scale Replica environments.
Productionize research: Ship robust, documented ML components integrated with Replica tooling.
Collaborate cross-functionally: Engage with simulation, rendering, and infrastructure engineers to deliver end-to-end solutions.

Requirements

Advanced degree: MS or PhD in ML, computer vision, robotics, or related field.
Deep ML expertise: Experience with deep learning frameworks (e.g., PyTorch) and large model development.
Strong engineering skills: Experience taking ML prototypes into production quality code.
Experience with 3D vision or reconstruction: Demonstrated knowledge of modern 3D representation learning.
Generative model background: Experience with diffusion models or neural rendering.

Benefits

Competitive compensation: A base pay range of $150,000 - 180,000/yr, depending on your skills, qualifications, experience, and location.
Impactful work: The chance to contribute to the advancement of autonomous systems and AI.
Collaborative culture: A dynamic and supportive work environment where your ideas are valued.
Professional growth: Opportunities to learn and develop your skills in a cutting-edge field.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills

machine learningvideo-to-video diffusion models4D feed-forward reconstructiondeep learning frameworksPyTorchproduction quality code3D visionmodern 3D representation learninggenerative modelsneural rendering

Soft skills

collaborationcross-functional engagement

Certifications

MS in MLPhD in ML