Javelin Venture Partners
Computer Vision Researcher (VLM)

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Niantic Spatial
Software Engineering
London, UK
Posted on May 8, 2026
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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.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
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.


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If required by law, by submitting my job application I consent to the processing of my information as described in that Notice, including processing information I voluntarily disclose to Niantic Spatial, such as health or medical information, race or ethnicity data, and sexual orientation data and, in limited circumstances sharing information with third parties such as references and other third parties that assist in the hiring process.
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.
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