Senior Machine Learning Engineer, Diffusion & Reconstruction na Parallel Domain

About the role:

• We are seeking a Senior Machine Learning Engineer to advance the state of learned reconstruction for Replica. In this role, you will drive development of feed-forward and diffusion-based models for 3D and spatiotemporal reconstruction and work closely with cross-functional teams to integrate these models into production systems.

What you'll do:

• 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.

What you’ll bring:

• 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.

What will help you stand out:

• Hands-on experience: Demonstrated experience in developing and deploying production-level machine learning models.
• Research background: Familiarity with academic research in video diffusion models, LoRA fine-tuning, or feed-forward reconstruction.
• Industry knowledge: Understanding of the autonomous systems landscape and the potential applications of machine learning in this domain.
• Publication record: Publications in top-tier conferences or journals related to machine learning.

What we offer:

• 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.