At a Glance
- Tasks: Lead groundbreaking research in geospatial AI and bridge 3D vision with language.
- Company: Join Niantic Spatial, a leader in innovative geospatial technology.
- Benefits: Competitive salary, flexible work environment, and opportunities for professional growth.
- Other info: Collaborative culture with a focus on mentorship and innovation.
- Why this job: Shape the future of AI and spatial intelligence while making a real-world impact.
- Qualifications: PhD in Computer Vision or related field with 4+ years of ML research experience.
The predicted salary is between 70000 - 90000 £ per year.
At Niantic Spatial, we’re building the future of geospatial AI. Powered by a proprietary database of over 30 billion posed images and a groundbreaking third‑generation digital map, our mission is to develop spatial intelligence that helps both humans and machines better understand, navigate, and engage with the physical world. Our high‑fidelity mapping technology unlocks a new dimension of interaction—laying the foundation for AI to truly comprehend and operate within real‑world environments. Join us as we build a living model of the world that people and machines can talk to.
As a Computer Vision Researcher with experience in Large Language Models (LLMs), you will bridge the gap between 3D computer vision LLMs, creating a unified framework where machines can reason about their surroundings. By linking spatial geometry directly to language, you will enable our systems to perform context‑aware navigation and answer complex, open‑ended questions about the physical world.
Responsibilities
- Architect Semantic Grounding: Lead research into cross‑modal grounding that connects 3D spatial features with language embeddings, enabling the LGM to "understand" object relationships and environmental context.
- Scale "Understand" Capabilities: Develop and deploy algorithms for continuous semantics, allowing our 3D maps to evolve and improve their situational awareness as new ground‑level and aerial data is ingested.
- Agentic Frameworks: Build the "spatial brain" for Embodied AI, enabling robots, drones and other machines to move beyond simple navigation to mission‑level reasoning.
- Multimodal Benchmarking: Define the standards for measuring "spatial common sense" in LLMs, creating evaluations that test a model’s ability to interpret and operate within complex 3D scenes.
- Technical Mentorship: Serve as the technical anchor for the London R&D hub, resolving architectural disagreements and mentoring the next generation of researchers in the fusion of 3D CV and NLP.
- Collaborative Innovation: Partner with Product leads to ensure the "Understand" API delivers high business value for enterprise customers in robotics, logistics, and field operations.
Required Qualifications
- Education: PhD (or equivalent) in Computer Vision, Machine Learning, or Robotics with a focus on Multimodal/Semantic understanding.
- Years of Experience: 4+ years of experience in ML research, with a proven track record of shipping models that bridge 3D Vision and Language.
- Technical Depth: Expert knowledge of 3D Geometry (SfM, SLAM, VPS) and Transformer‑based architectures (VLMs).
- Research Impact: Multiple first‑author publications at top‑tier venues (CVPR, NeurIPS, ICLR) focusing on VLMs, scene understanding or semantic segmentation.
- Implementation Mastery: Ability to write production‑quality research code in PyTorch or JAX and manage large‑scale data pipelines.
- Required In‑Office Days: 3 days per week.
Plus If
- Experience with Gaussian Splatting or NeRFs for semantic scene representation.
- Background in robotics (ROS) or building agentic systems that interact with physical environments.
- Experience with "open‑set" recognition and Zero‑Shot learning.
Niantic Spatial is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with reasonable accommodation during the application process, please contact your recruiter.
Computer Vision Researcher (VLM) in London employer: Niantic Spatial, Inc.
At Niantic Spatial, we pride ourselves on fostering a collaborative and innovative work culture that empowers our employees to push the boundaries of geospatial AI. Located in London, our R&D hub offers exceptional growth opportunities through technical mentorship and hands-on projects, allowing you to make a meaningful impact in the field of computer vision and language models. Join us to be part of a diverse team dedicated to building cutting-edge technology that transforms how humans and machines interact with the world.
StudySmarter Expert Advice🤫
We think this is how you could land Computer Vision Researcher (VLM) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to 3D computer vision and language models. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both technical and non-technical team members.
✨Tip Number 4
Don't forget to apply through our website! We love seeing applications directly from candidates who are excited about joining us at StudySmarter. Plus, it shows you're genuinely interested in being part of our team!
We think you need these skills to ace Computer Vision Researcher (VLM) in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to highlight your experience in 3D computer vision and language models. We want to see how your skills align with our mission at Niantic Spatial, so don’t hold back on showcasing relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about bridging the gap between 3D vision and language. We love seeing enthusiasm and a clear understanding of our goals, so let your personality come through.
Showcase Your Research Impact:If you've got publications, make sure to mention them! Highlighting your research impact, especially in top-tier venues, will help us see your expertise in action. We’re keen on candidates who can demonstrate their contributions to the field.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, it shows you’re serious about joining our team at Niantic Spatial.
How to prepare for a job interview at Niantic Spatial, Inc.
✨Know Your Stuff
Make sure you brush up on your knowledge of 3D geometry, machine learning, and large language models. Be ready to discuss your past research and how it relates to the role at Niantic Spatial. They’ll want to see that you can connect the dots between your experience and their mission.
✨Showcase Your Projects
Prepare to talk about your previous projects, especially those involving multimodal understanding or semantic grounding. Bring examples of your work, like publications or code snippets, to demonstrate your expertise and how you’ve tackled similar challenges in the past.
✨Think Like a Collaborator
Niantic Spatial values collaborative innovation, so be ready to discuss how you’ve worked with product leads or other teams in the past. Highlight your ability to mentor others and resolve technical disagreements, as this will show you’re a team player who can contribute to their R&D hub.
✨Prepare for Technical Questions
Expect some deep technical questions related to your field. Brush up on concepts like Gaussian Splatting, NeRFs, and agentic systems. Practising coding problems in PyTorch or JAX could also give you an edge, as they’ll want to see your implementation skills in action.