Research Scientist specializing in quantum error correction at Quantinuum, developing software tools and conducting computational research with a strong emphasis on collaboration.
About the role
- Applied Scientist developing machine learning models for computer vision in film production. Enhancing AI-driven rendering and perception systems for seamless workflows.
Responsibilities
- Develop and enhance rendering, perception and compositing systems
- Design, fine-tune and implement advanced face detection, clustering, and compositing algorithms for DE long form pipelines.
- Optimize and scale training and inference systems for high-volume video processing.
- Translate research breakthroughs into robust, efficient production code.
- Conduct rapid experiments on state-of-the-art architectures (Transformers, diffusion models, 3DGS) to improve robustness and accuracy.
- Evaluate, benchmark, and document model performance against production metrics.
- Identify and resolve bottlenecks in existing AI workflows.
- Partner with Science, Engineering, and Product team members to ensure seamless integration of AI modules.
- Mentor other scientists, engineers and Product folk and contribute to the technical roadmap for character prep & vubbing group.
- Advocate for scalable, production-ready solutions that directly enhance user experience.
Requirements
- Strong experience developing and applying computer vision or machine learning methods for visual understanding problems (e.g., face perception, motion/pose estimation, or video analysis).
- OR
- Experience developing neural rendering or 3D generation systems (e.g., novel view synthesis, scene reconstruction, or generative models for photorealistic rendering).
- A strong product mindset — motivated by building systems that deliver tangible value to users, not just technical novelty.
- Comfortable working at both the algorithmic and implementation levels, from model design and optimization to large-scale data processing and integration in production systems.
- Proficiency in Python, with a strong foundation in computer science and problem-solving.
- Expertise with deep learning frameworks (PyTorch) and vision tools (OpenCV).
- MSc/PhD in Visual Computing, Computer Science, or a related field, or equivalent professional experience.
- Hands-on experience with deep learning approaches such as Vision Transformers, GANs, diffusion models, VAEs, or emerging methods (e.g., 3DGS).
- Bonus points for:
- Experience developing multi-modal systems that integrate audio, text, and visual inputs.
- Experience working with cross-functional product and engineering teams.
Benefits
- Autonomy
- A hybrid working environment
- Competitive Salary
- All permanent employees receive generous stock options
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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