Computer Vision/Machine Learning Research Scientist (Spatial AI)
Meta
Computer Vision/Machine Learning Research Scientist (Spatial AI)
Job Description
The Reality Labs team at Meta is looking for Computer Vision Researchers to support our Spatial AI team as we build towards our goal to transform the way people come together to interact, work and play. We explore, develop and deliver cutting-edge technologies that serve as the foundations for the current and future Reality Labs products including VR, AR, smart-glasses, AI agents, and robotics. We are committed to driving the state-of-the-art forward through innovation across ML perception in 2D and 3D, for both primitives (e.g. depth, segmentation, and semantic keypoints) as well as high-level (e.g. shape inference, 3D reconstruction, context/semantic understanding). The ideal candidate will help us develop the next generation of spatial and contextualized AI, and lay the foundations for a new computing paradigm that is built from the ground up to understand the physical world from egocentric devices. We are looking for experts in areas such as vision-language models, agentic AI, learning from demonstration, and representation learning. The potential to change the world is immense -- and we're just getting started. We encourage you to apply and join us!
Locations
- Zurich, Switzerland, CHE
Salary
Estimated Salary Rangemedium confidence
12,000,000 - 25,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Computer Visionintermediate
- Machine Learningintermediate
- Spatial AIintermediate
- Virtual Realityintermediate
- Augmented Realityintermediate
- 3D Perceptionintermediate
- Depth Estimationintermediate
- Image Segmentationintermediate
- Semantic Keypointsintermediate
- Shape Inferenceintermediate
- 3D Reconstructionintermediate
- Contextual Understandingintermediate
- Semantic Understandingintermediate
- Vision-Language Modelsintermediate
- Agentic AIintermediate
- Learning from Demonstrationintermediate
- Representation Learningintermediate
- AI Agentsintermediate
- Roboticsintermediate
Required Qualifications
- PhD degree in the field of Artificial Intelligence, Robotics, Computer Vision, Machine Learning, Natural Language Understanding, or equivalent practical experience Significant industry experience in relevant areas Leadership experience driving high-risk, high reward projects scientifically, including managing a team of research scientists and communicating to leadership Proven track record of achieving results as demonstrated by grants, fellowships, patents, as well as first-authored publications at conferences such as CVPR, ICCV, NeurIPS, or similar Experience handling concurrent projects where timelines may be ambiguous or changing, and prioritizing by balancing required effort with resulting impact Experience in Python Experience with distributed systems or on-device algorithm development Experience communicating research for public audiences of peers Experience working and communicating cross-functionally in a team environment Significant industry experience in relevant robotics related research areas, preferably large multimodal models, agentic AI, 3D reconstruction with deep learning methods Leadership and interpersonal communication experience in working across many disciplines, driving best practices, and mentorship Experience with deep learning frameworks (such as pytorch, tensorflow) and Python Experience solving complex problems and comparing alternative solutions, tradeoffs, and different perspectives to determine a path forward (experience)
Responsibilities
- Design and development of novel machine learning algorithms to solve problems in areas such as: vision-language models, agentic AI for multimodal systems, foundation models, 3D reconstruction with deep learning methods, depth estimation, semantic segmentation, 2D and 3D semantic key point detection, and object tracking Define, build, and benchmark new capabilities needed for the next generation of AI Communicate cross-functionally Drive the team's goals and technical direction to pursue technical opportunities Lead and collaborate with multidisciplinary engineering and research teams to develop technologies from early exploration and incubation to production
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Computer Vision/Machine Learning Research Scientist (Spatial AI)
Meta
Computer Vision/Machine Learning Research Scientist (Spatial AI)
Job Description
The Reality Labs team at Meta is looking for Computer Vision Researchers to support our Spatial AI team as we build towards our goal to transform the way people come together to interact, work and play. We explore, develop and deliver cutting-edge technologies that serve as the foundations for the current and future Reality Labs products including VR, AR, smart-glasses, AI agents, and robotics. We are committed to driving the state-of-the-art forward through innovation across ML perception in 2D and 3D, for both primitives (e.g. depth, segmentation, and semantic keypoints) as well as high-level (e.g. shape inference, 3D reconstruction, context/semantic understanding). The ideal candidate will help us develop the next generation of spatial and contextualized AI, and lay the foundations for a new computing paradigm that is built from the ground up to understand the physical world from egocentric devices. We are looking for experts in areas such as vision-language models, agentic AI, learning from demonstration, and representation learning. The potential to change the world is immense -- and we're just getting started. We encourage you to apply and join us!
Locations
- Zurich, Switzerland, CHE
Salary
Estimated Salary Rangemedium confidence
12,000,000 - 25,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Computer Visionintermediate
- Machine Learningintermediate
- Spatial AIintermediate
- Virtual Realityintermediate
- Augmented Realityintermediate
- 3D Perceptionintermediate
- Depth Estimationintermediate
- Image Segmentationintermediate
- Semantic Keypointsintermediate
- Shape Inferenceintermediate
- 3D Reconstructionintermediate
- Contextual Understandingintermediate
- Semantic Understandingintermediate
- Vision-Language Modelsintermediate
- Agentic AIintermediate
- Learning from Demonstrationintermediate
- Representation Learningintermediate
- AI Agentsintermediate
- Roboticsintermediate
Required Qualifications
- PhD degree in the field of Artificial Intelligence, Robotics, Computer Vision, Machine Learning, Natural Language Understanding, or equivalent practical experience Significant industry experience in relevant areas Leadership experience driving high-risk, high reward projects scientifically, including managing a team of research scientists and communicating to leadership Proven track record of achieving results as demonstrated by grants, fellowships, patents, as well as first-authored publications at conferences such as CVPR, ICCV, NeurIPS, or similar Experience handling concurrent projects where timelines may be ambiguous or changing, and prioritizing by balancing required effort with resulting impact Experience in Python Experience with distributed systems or on-device algorithm development Experience communicating research for public audiences of peers Experience working and communicating cross-functionally in a team environment Significant industry experience in relevant robotics related research areas, preferably large multimodal models, agentic AI, 3D reconstruction with deep learning methods Leadership and interpersonal communication experience in working across many disciplines, driving best practices, and mentorship Experience with deep learning frameworks (such as pytorch, tensorflow) and Python Experience solving complex problems and comparing alternative solutions, tradeoffs, and different perspectives to determine a path forward (experience)
Responsibilities
- Design and development of novel machine learning algorithms to solve problems in areas such as: vision-language models, agentic AI for multimodal systems, foundation models, 3D reconstruction with deep learning methods, depth estimation, semantic segmentation, 2D and 3D semantic key point detection, and object tracking Define, build, and benchmark new capabilities needed for the next generation of AI Communicate cross-functionally Drive the team's goals and technical direction to pursue technical opportunities Lead and collaborate with multidisciplinary engineering and research teams to develop technologies from early exploration and incubation to production
Tags & Categories