At a Glance
- Tasks: Join a team developing cutting-edge 3D reconstruction technology and conduct original research in computer vision.
- Company: Innovative tech company focused on transforming physical AI with a collaborative culture.
- Benefits: Competitive salary, bonus, equity, excellent benefits, and hybrid work model.
- Other info: Opportunity for career growth in a dynamic environment with real-world impact.
- Why this job: Work with top researchers and publish at leading conferences while impacting real-world applications.
- Qualifications: PhD or equivalent experience in Computer Vision, strong research background, and excellent Python skills.
The predicted salary is between 100000 - 125000 £ per year.
Location: London (Hybrid – 3 days per week)
Type: Full-time
Salary: £100,000–£125,000 + Bonus + Equity + Excellent Benefits
Help Build the Future of Physical AI. We're building cutting-edge technology that enables machines to understand, navigate and interact with the physical world. Using one of the world's largest geospatial datasets, our platform transforms everyday imagery into highly detailed 3D reconstructions and powers next‑generation spatial intelligence for robotics, industrial automation, infrastructure and AI applications.
We're looking for a Computer Vision Research Engineer to join our London-based research team and help develop state‑of‑the‑art 3D reconstruction technology that moves rapidly from research into production. This is an opportunity to work alongside internationally recognised researchers across computer vision, machine learning, graphics and robotics while publishing at leading conferences and shipping technology used by enterprise customers.
What You'll Be Working On:
- 3D Reconstruction
- Structure‑from‑Motion (SfM)
- Neural Scene Representations
- 3D Gaussian Splatting
- Geometric Deep Learning
- Feed‑forward Models
- Spatial Foundation Models
You’ll also:
- Conduct original research in computer vision and machine learning
- Design and evaluate novel algorithms
- Build large‑scale experimentation and benchmarking frameworks
- Work closely with engineering teams to transition research into production
- Develop technology that operates under real‑world capture conditions and hardware constraints
- Publish research at leading conferences including CVPR, ICCV, ECCV, SIGGRAPH and related venues
What We're Looking For:
- PhD in Computer Vision, Machine Learning, Robotics, Computer Science, Mathematics, Physics or a related field (or equivalent industry experience)
- Strong research background in 3D Computer Vision, including one or more of:
- 3D Reconstruction
- Structure‑from‑Motion
- SLAM
- Depth Estimation
- Novel View Synthesis
- Strong publication record at top‑tier research conferences
- Excellent Python and PyTorch skills
- Evidence of taking research from concept into real‑world systems (production products, open‑source projects or deployed research)
- Ability to independently lead research projects from idea through experimentation and publication
StudySmarter Expert Advice🤫
We think this is how you could land Computer Vision Research Engineer in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at DeepRec.ai or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to DeepRec.ai.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like DeepRec.ai.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like DeepRec.ai that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Computer Vision Research Engineer in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at DeepRec.ai.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at DeepRec.ai and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at DeepRec.ai
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If DeepRec.ai uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
