At a Glance
- Tasks: Research and develop cutting-edge AI algorithms for Augmented Reality and spatial perception.
- Company: Join Zebra, a community of innovators redefining the future of work.
- Benefits: Enjoy 25 days vacation, volunteer time off, and competitive bonuses.
- Other info: Flexible hybrid work model with excellent career growth opportunities.
- Why this job: Make a real impact in AI while collaborating with global experts.
- Qualifications: Master's or Ph.D. in relevant fields with hands-on SLAM experience.
The predicted salary is between 63000 - 77000 £ per year.
Overview
At Zebra, we are a community of innovators who come together to create new ways of working.
United by curiosity and a culture of caring, we develop smart solutions that anticipate our customer's and partner's needs and solve their challenges.
Being part of Zebra Nation means you are seen, heard, valued, and respected.
Drawing from our unique perspectives, we collaborate to deliver on our purpose.
Here you are part of a team pushing boundaries today to redefine the work of tomorrow for organizations, their employees, and those they serve.
You’ll have opportunities to learn and lead in a forward-thinking environment, defining your path to a fulfilling career while channeling your skills toward causes you care about‑locally and globally.
Come make an impact every day at Zebra.
What We're Looking For
We are looking for an
AI Research Scientist specialising in SLAM, Visual‑Inertial Odometry (VIO), and 3D Spatial Perception to join our central CTO Group.
In this horizontal, high‑impact organisation, you will collaborate with cross‑functional business units across the globe and work closely with our London‑based research hub of ~15 AI specialists.
In this role, you will be bridging the gap between innovation and on‑device execution—prototyping new algorithms, training spatial models, and optimising them to run directly on resource‑constrained mobile edge devices to power next‑generation Augmented Reality (AR), enterprise vision, and edge intelligence.
You will be based at our central London office (Endeavour House, Shaftesbury Avenue, WC2H 8JR) on a flexible hybrid model—collaborating in person 3 days a week, with 2 days working from home.
Responsibilities
- Research, design, and implement robust Visual‑Inertial Odometry (VIO), 6‑Do F camera pose estimation, and monocular SLAM pipelines tailored for resource‑constrained edge hardware.
- Develop advanced algorithms for spatial localisation, multi‑view ray triangulation, sensor fusion (IMU + Camera), and plane‑fitting (e. g., RANSAC, Pn P) to achieve sub‑centimetre overlay accuracy and eliminate tracking drift.
- Translate research papers into real‑time algorithms, optimising neural networks and spatial pipelines for low‑latency execution on mobile NPUs, DSPs, and GPUs.
- Build spatial foundations that deliver seamless on‑device AR experiences, barcode/shelf product recognition, OCR, and multi‑modal edge AI capabilities without relying on cloud connectivity.
- Partner with global hardware, software, and product engineering teams to integrate your models into commercial product roadmaps.
Qualifications
- Master's or Ph. D. in Computer Science, Robotics, Electrical Engineering, or a related quantitative field with a specialised focus on Computer Vision, Spatial AI, or Robotics.
- At least 2 years of hands‑on experience in research and development of SLAM / Spatial tracking systems.
- Deep theoretical understanding and hands‑on implementation of SLAM (Simultaneous Localisation and Mapping) and VIO (Visual‑Inertial Odometry).
- Strong foundation in 6‑Do F pose tracking, sensor fusion (IMU + Vision), and camera calibration (intrinsic/extrinsic parameters).
- 3D geometric computer vision: ray‑plane intersections, epipolar geometry, bundle adjustment, and monocular depth estimation.
- High proficiency in C++ and/or Python, along with standard ML and Computer Vision frameworks (e. g., Py Torch, Open CV, ROS/GTSAM/Ceres Solver).
Benefits
- 25 days of vacation
- Up to 32 hours paid time off per year to volunteer with a charity of your choice
- Reward & Recognition scheme—earn points to spend online
- Training and personal development in soft skills and hard skills, access to our internal learning portal and internal career opportunities within Zebra departments
- Annual bonuses based on financial results
- Yearly salary increases according to individual performance
- Employee referral bonus for bringing New Talent to Zebra
- Pension Scheme with a matched contribution up to 7%
- Private medical and dental cover
- Access to an innovative online learning platform
- Cycle to work scheme
- Employee Assistance Program
Incentive Compensation
In addition to base pay, Zebra offers this role the opportunity to earn a performance‑based annual cash incentive, at a target equal to 10% of base pay, in accordance with the terms of the applicable incentive plan.
AI Research Scientist employer: NCSL International
Join a dynamic and innovative team as a Surveillance Analyst, where your expertise in SMARTS will be valued in a collaborative work culture that prioritises compliance and integrity. Located in a vibrant financial hub, the company offers competitive salaries, comprehensive benefits, and ample opportunities for professional growth, ensuring you can thrive in your career while contributing to the firm's mission of maintaining market integrity.
StudySmarter Expert Advice🤫
We think this is how you could land AI Research Scientist
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We think you need these skills to ace AI Research Scientist
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 NCSL International.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at NCSL International 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 NCSL International
✨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 NCSL International 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.
