At a Glance
- Tasks: Design and deploy ML models for cutting-edge AR wearables.
- Company: Join Snap's innovative Spectacles team in London.
- Benefits: Enjoy comprehensive medical coverage and paid parental leave.
- Other info: Collaborate with a world-class team in a dynamic environment.
- Why this job: Shape the future of wearable computing and AR technology.
- Qualifications: 5+ years experience in computer vision and programming skills.
The predicted salary is between 63000 - 77000 £ per year.
Overview
As a Computer Vision & ML Engineer on the Spectacles team in London, you will help advance photon-efficient, event-driven imaging for next-generation AR wearables.
You’ll collaborate with Snap’s hardware and software groups to design and deploy ML models and CV algorithms, contributing to tracking, depth estimation, and SLAM in high-temporal-resolution data.
This role blends cutting-edge imaging research with practical implementations to enable camera-first experiences.
You join a world-class team shaping wearable computing and AR glasses.
- Pay / Benefits
- paid parental leave
- comprehensive medical coverage
- emotional and mental health support programs
- compensation packages linked to Snap’s long-term success
Responsibilities
- Design, train, and deploy machine learning models and CV algorithms for photon-efficient, event-driven imaging systems
- Advance tracking, depth estimation, and SLAM using high-temporal-resolution event-driven data
- Develop novel photon-efficient imaging features for AR glasses
- Explore ML and probabilistic techniques to boost speed, noise robustness, and accuracy of CV systems
- Contribute to detection capabilities (face, hand, body) for AR systems
- Key requirements
- 5+ years of post-Bachelor’s relevant experience; or Master’s degree + 4+ years; or Ph D + 2 years
- Experience with computer vision for photon-efficient or event-driven imaging systems (e. g. VIO, SLAM, Hand tracking)
- 5+ years programming in C++ and Python (e. g. Py Torch, Tensor Flow)
- Strong foundation in CV, ML, and statistical signal processing
- Solid math background in 3D geometry, probability, statistics, and linear algebra
- Ability to translate ideas into clean, fast, reliable code
- Attention to detail and strong communication; outstanding problem-solving skills
- Attention to detail
- Clear communication
- Problem-solving
- Photon-efficient, event-driven imaging
- Computer vision and machine learning
- VIO/SLAM/Hand tracking
Computer Vision & Machine Learning Engineer, Photon-Efficient Event-Driven Imaging in London employer: SNAP
At Snap, we pride ourselves on fostering a dynamic and inclusive work environment that empowers our employees to innovate and excel. As a Senior Software Engineer in the Specs team, you will have the opportunity to work on cutting-edge computer vision technologies while enjoying comprehensive benefits, including paid parental leave and mental health support. Our commitment to employee growth and collaboration ensures that you will thrive in your role, contributing to meaningful projects that shape the future of technology.
StudySmarter Expert Advice🤫
We think this is how you could land Computer Vision & Machine Learning Engineer, Photon-Efficient Event-Driven Imaging 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 SNAP 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 SNAP.
✨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 SNAP.
✨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 SNAP 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 & Machine Learning Engineer, Photon-Efficient Event-Driven Imaging 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 SNAP.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at SNAP 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 SNAP
✨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 SNAP 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.
