Machine Learning Engineering Intern in London

Machine Learning Engineering Intern in London

London Internship 60000 - 80000 £ / year (est.) No working from home possible
Snapchat

At a Glance

  • Tasks: Join the Spectacles AR team to develop cutting-edge machine learning models for augmented reality.
  • Company: Snap Inc, a leading tech company revolutionising communication through innovative products.
  • Benefits: Enjoy competitive pay, health coverage, and a supportive community focused on your well-being.
  • Other info: Collaborative office culture with excellent career growth opportunities and a commitment to diversity.
  • Why this job: Make an impact in AR technology while learning from industry experts in a dynamic environment.
  • Qualifications: Pursuing a degree in a technical field with strong Python skills and a passion for machine learning.

The predicted salary is between 60000 - 80000 £ per year.

Snap Inc is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together. The Company’s three core products are Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world; Lens Studio, an augmented reality platform that powers AR across Snapchat and other services; and its AR glasses, Spectacles. The Spectacles team is pushing the boundaries of technology to bring people closer together in the real world.

We are looking for a Machine Learning Engineering Intern to join the Spectacles AR engineering team at Snap Inc!

What you’ll do:

  • Join the Spectacles AR team in the London, UK office for a 13-week Summer 2026 Machine Learning Engineering Internship.
  • Contribute to the Spectacles software organization, which is dedicated to developing the perception and understanding systems necessary for intelligent AR experiences on Spectacles.
  • Work on a technical project that aligns with Spectacles product and research needs, focused on scene understanding for AR experiences.
  • Prototype, train, and evaluate machine learning models for computer vision and multimodal understanding, using Python and modern deep learning frameworks.
  • Contribute to models, tooling, and algorithms in geometric scene understanding, 3D reconstruction, semantic scene understanding, visual localisation, and connecting scene understanding to language for richer, more semantic AR interactions.
  • Partner closely with your mentor and teammates across Spectacles software and other cross-functional teams to integrate your work into production-facing systems.
  • Learn and apply new software engineering and machine learning skills in a fast-paced, collaborative environment.

Knowledge, Skills & Abilities:

  • Strong computer science fundamentals and problem-solving skills.
  • Proficiency in Python for data processing, model development, and experimentation.
  • Familiarity with at least one deep learning framework (e.g. PyTorch, TensorFlow, or JAX).
  • Understanding of core concepts in machine learning and at least one of: Computer Vision (e.g. image classification, detection, segmentation, depth estimation, optical flow, 3D geometry), or Natural Language / LLMs (e.g. sequence modeling, transformers, language model fine-tuning, vision-language models).
  • Ability to understand, debug, and improve existing code as well as develop new algorithms using advanced computer vision and machine learning techniques.
  • Ability to collaborate with other engineers and cross-functional partners, and communicate technical ideas clearly.
  • Comfortable working in a Linux-based development environment.

Minimum Qualifications:

  • Currently enrolled in a BS, MS program in a technical field such as Computer Science, Electrical/Computer Engineering, Mathematics, or a related discipline, with a graduation date no sooner than December 2026.
  • Graduating between December 2026 and Spring 2027.
  • Must be able to start in office in May or June 2026 for a 13-week internship.

Preferred Qualifications:

  • Coursework or hands-on project experience in machine learning or deep learning.
  • Experience writing, documenting and debugging high quality code in Python.
  • Experience with standard developer practices (version control, rigorous testing, documentation standards).

At Snap Inc. we believe that being together in person helps us build our culture faster, reinforce our values, and serve our community, customers and partners better through dynamic collaboration. To reflect this, we practice a “default together” approach and expect our team members to work in an office 4+ days per week.

Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws.

Our Benefits: Snap Inc. is its own community, so we’ve got your back! We do our best to make sure you and your loved ones have everything you need to be happy and healthy, on your own terms. Our benefits are built around your needs and include paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages that let you share in Snap’s long-term success!

Machine Learning Engineering Intern in London employer: Snapchat

Snap Inc. is an exceptional employer that fosters a vibrant and inclusive work culture, particularly within its London office where the Machine Learning Engineering Intern will thrive. With a strong emphasis on collaboration and innovation, employees benefit from comprehensive support including paid parental leave, mental health resources, and opportunities for professional growth in cutting-edge technology. Joining Snap means being part of a community dedicated to empowering individuals through creative expression and transformative AR experiences.

Snapchat

Contact Details:

Snapchat Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Machine Learning Engineering Intern in London

Join Data-Science Meetups

Get yourself along to local data-science meetups or workshops. They're goldmines for networking, and you'll learn from industry pros who might just point you in the direction of internships. Plus, discussing the latest trends with like-minded individuals can really amp up your game.

Utilise University Career Services

Check in with your uni's career services since they often have connections with companies looking for interns. They might even organise information sessions with firms, which can be a great chance for you to learn more about potential internships and make some key contacts.

Show Off Your Stuff on GitHub

If you're into data science, having a GitHub profile with your projects is essential. Make sure your portfolio is public and showcases your best work! Recruiters love to see your coding skills and problem-solving approach, and it’s a brilliant way to stand out.

Apply Directly on Our Website

Don’t forget to check out the internships listed on our site! It's always a good idea to apply directly through our website because it makes your application easier for our team to find, and you might just catch the hiring manager’s eye by showcasing exactly what you're passionate about in data science.

We think you need these skills to ace Machine Learning Engineering Intern in London

Machine Learning
Computer Vision
Deep Learning Frameworks (e.g. PyTorch, TensorFlow, JAX)
Python Programming
Data Processing
Model Development
3D Reconstruction

Some tips for your application 🫡

Show Off Your Technical Skills:For a data science internship, we want to see those analytical skills shine! List your programming languages, like Python or R, and make sure to highlight any relevant projects or courses you've completed. If you've dabbled with tools like Pandas, NumPy, or machine learning algorithms, don’t hold back – include those in your CV!

Share Your Curiosity in Your Cover Letter:As an intern, your motivation and eagerness to learn are key! In your cover letter, talk about specific data science concepts that excite you and how this internship at Snapchat will help you grow. Share what you hope to achieve and how you plan to tackle real-world data problems - we love enthusiasm!

Include Any Relevant Certifications:If you've earned any certifications, such as from Coursera or DataCamp, make sure to include these in your application. They show us that you're proactive and committed to expanding your data science skillset. This could make a real difference in how we assess your application!

Keep It Relevant and Concise:Remember, as an intern, you don’t need to have decades of experience. Focus on showcasing relevant coursework, personal projects, or even related volunteer work in data science. Keep your CV and cover letter concise but impactful – we appreciate clear and straightforward communication!

How to prepare for a job interview at Snapchat

Brush Up on Your Coding Skills

As a data science intern, you might get grilled on your programming skills. Expect to tackle some coding challenges using languages like Python or R. We recommend practising basic algorithms or data manipulation tasks so you can show off your tech skills with confidence.

Show Off Your Projects

Prepare to discuss any projects you’ve done, whether in your studies or on your own time. Having a strong portfolio of data analyses or machine learning models will really set you apart. We can use platforms like GitHub to showcase your work to impress Snapchat.

Know Your Stats and ML Basics

Brush up on your statistics and machine learning concepts because interviewers love to dig into this! Be ready to explain your understanding of algorithms or how you would approach a given data problem. This will highlight your theoretical background alongside your practical skills.

Be Eager to Learn and Adapt

Internships are all about potential and growth. Make sure you convey your eagerness to learn and adapt to new tools or methodologies. Show Snapchat that you’re not just looking for experience, but that you're keen to contribute and grow within the team.