Machine Learning Engineer

Minimal
London
1 day ago
Create job alert

Machine Learning Engineer page is loaded## Machine Learning Engineerlocations:

London, United Kingdomtime type:

Full timeposted on:

Posted Todayjob requisition id:

R0043783is 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 , a visual messaging app that enhances your relationships with friends, family, and the world; , an augmented reality platform that powers AR across Snapchat and other services; and its AR glasses, .teams build fun and technically sophisticated products that reach hundreds of millions of Snapchatters around the world, every day. We’re deeply committed to the well-being of everyone in our global community, which is why are at the root of everything we do. We move fast, with precision, and always execute with privacy at the forefront.We're looking for a Machine Learning Engineer to join the Consumer Gen AI Product MLE team at Snap!What you’ll do:* Develop ML-products and AI Lenses that serve millions of Snapchatters on a daily basis, with a primary focus on image and video generation and editing, as well as LLMs* Build cutting-edge augmented reality experiences with diffusion/flow matching models and GANs* Work on state of the art GenAI pipelines for image and video generation* Extensively collaborate with Product, Software Engineering, Lens Content and Data Science teams to prototype new ideas, integrate ML models and APIs into production, and refine them through A/B testing and user feedback* Actively monitor the market and research landscape for new developments in Gen AI, evaluate open-source models and third-party AI APIs/services to inform build-vs-buy decisions to leverage the best available tools (or iterate on them) to keep Snap’s products at the cutting edge* Evaluate open-source Gen AI models and APIsKnowledge, Skills & Abilities:* A proven passion for machine learning; you stay up-to-date with research and are excited about prototyping new ideas quickly* Knowledge of mathematics and deep learning foundations* Excellent verbal and written communication skills, with meticulous attention to detail* Ability to work independently* Ability leading and executing large, complex technical initiativesMinimum Qualifications:* Strong background in Machine Learning* Experience supporting applied machine learning teams that work closely with Product* Strong programming skills in Python or C++* Bachelor’s Degree in a technical field such as computer science, mathematics, statistics or equivalent years of engineering experience in one or more of the following: neural rendering, generative models, segmentation, object detection, classification, tracking, or other related applications of deep learning* Track record of delivery ML-based backend products at scale in rapidly changing, highly collaborative, multi-stakeholder environments* Track of record of collaboration with Product, Design and Data science functions to build consumer-facing ML-based products* History of involvement in product roadmappingPreferred Qualifications:* Knowledge of computer graphics foundations* Experience with visual Gen AI models for Image and Video generation and Editing* Experience with evaluating the visual quality of Image and Video models* Track record of successful projects in GenAI field* Proven track of closely collaborating with Product, Design and Software Engineering teams for launching consumer-facing Gen AI or ML-powered products* Ability to proactively learn new concepts and apply them at workIf you have a disability or special need that requires accommodation, please don’t be shy and provide us some ."Default Together" Policy at Snap: 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. At Snap, we believe that having a team of diverse backgrounds and voices working together will enable us to create innovative products that improve the way people live and communicate. 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. EOE, including disability/vets.: 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!
#J-18808-Ljbffr

Related Jobs

View all jobs

Machine Learning Engineer (Forward Deployed)

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.