Machine Learning Engineering Intern

Job description

Snap Inc is a technology company focused on camera technology and augmented reality.

The Spectacles team is pushing the boundaries of technology to bring people closer together in the real world. Our fifth‐generation Spectacles, powered by Snap OS, showcase how standalone, see‐through AR glasses make playing, learning, and working better together.

Snap's camera supports real friendships through visual communication, self‐expression, and storytelling. Moving forward, our camera will play a transformative role in how people experience the world, combining what they see in the real world with all that's available to them in the digital world.

Machine Learning Engineering Intern – Spectacles AR TeamJoin the Spectacles AR team in the London, UK office for a 13‐week Summer 2026 Machine Learning Engineering Internship. As an intern, you will contribute to the Spectacles software organization, which is dedicated to developing the perception and understanding systems needed for intelligent AR experiences on Spectacles.

What you'll do

Work on a technical project aligned 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).

BenefitsOur benefits 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.

Snap Inc. Is an equal opportunity employer, 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. EOE, including disability/vets.

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Extra information

Status

Closed

Education Level

Secondary School

Location

London

Type of Contract

Full Time Jobs

Full UK/EU driving license preferred

No

Car Preferred

No

Must be eligible to work in the EU

No

Cover Letter Required

No

Languages

English