At a Glance
- Tasks: Develop innovative ML products and AI Lenses for millions of Snapchat users.
- Company: Join Snap Inc, a leading tech company revolutionising communication through the camera.
- Benefits: Enjoy comprehensive medical coverage, paid parental leave, and mental health support.
- Other info: Collaborative environment with excellent career growth opportunities.
- Why this job: Make a real impact in Gen AI while working on cutting-edge technology.
- Qualifications: Strong background in Machine Learning and programming skills in Python or C++.
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 operates Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world, and Specs Inc., a wholly-owned subsidiary dedicated to making computing more human, in addition to Bitmoji, Saturn, and other digital services.
We're looking for a Senior 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.
- Work on state of the art GenAI pipelines for image and video generation. Ship a consumer-facing solution within weeks.
- 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 APIs.
Knowledge, 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 initiatives.
Minimum Qualifications:
- Strong background in Machine Learning.
- 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 or computer vision.
Preferred 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.
- Ability to proactively learn new concepts and apply them at work.
If you have a disability or special need that requires accommodation, please don’t be shy and provide us some information.
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.
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 Engineer, Consumer Gen AI Product Engineering 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 Machine Learning Engineer, Consumer Gen AI Product Engineering in London
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We think you need these skills to ace Machine Learning Engineer, Consumer Gen AI Product Engineering in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Craft a Tailored Cover Letter:For a full-time role at SNAP, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at SNAP. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at SNAP
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at SNAP!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
