At a Glance
- Tasks: Create innovative ML products for millions of Snapchatters, focusing on image and video generation.
- Company: Join a leading tech company at the forefront of Gen AI and augmented reality.
- Benefits: Enjoy paid parental leave, comprehensive medical coverage, and mental health support.
- Other info: Collaborative environment with opportunities for rapid career growth and learning.
- Why this job: Make a real impact by developing cutting-edge technology that enhances user experiences.
- Qualifications: Strong background in machine learning and programming skills in Python or C++ required.
The predicted salary is between 70000 - 90000 £ per year.
Responsibilities
- 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 large language models.
- Build cutting‑edge augmented reality experiences with diffusion and flow‑matching models.
- Work on state‑of‑the‑art Gen AI 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.
- Evaluate open‑source Gen AI models and APIs.
- Knowledge, Skills & Abilities
- A proven passion for machine learning and a commitment to staying up‑to‑date with research and prototyping new ideas quickly.
- Strong knowledge of mathematics and deep learning foundations.
- Excellent verbal and written communication skills, with meticulous attention to detail.
- Ability to work independently.
- Ability to lead and execute 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 engineering experience in one or more of the following: neural rendering, generative models, segmentation, object detection, classification, tracking, or other related deep learning or computer vision applications.
- 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 the Gen AI field.
- Ability to proactively learn new concepts and apply them at work.
Benefits
- Paid parental leave.
- Comprehensive medical coverage.
- Emotional and mental health support programs.
- Compensation packages that allow employees to share in Snap’s long‑term success.
Snap is proud to be an equal opportunity employer, and is 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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Machine Learning Engineer, Consumer Gen AI Product Engineering 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
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We think you need these skills to ace Machine Learning Engineer, Consumer Gen AI Product Engineering
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!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
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
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✨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.
