Senior Machine Learning Engineer, Diffusion & Reconstruction
Parallel Domain
full-time
Posted on:
Location Type: Hybrid
Location: Karlsruhe • Germany
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Job Level
Tech Stack
About the role
- 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: Dependent 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 learningPyTorchproduction quality code3D vision3D representation learninggenerative modelsneural rendering
Soft skills
collaborationcross-functional engagement
Certifications
MS in MLPhD in ML