At a Glance
- Tasks: Create amazing AR experiences using cutting-edge machine learning and AI technologies.
- Company: Join Snap, a leader in social media innovation and creativity.
- Benefits: Enjoy competitive pay, flexible work options, and opportunities for growth.
- Other info: Collaborative team environment with exciting projects and career advancement.
- Why this job: Make a real impact on millions of users with your creative tech skills.
- Qualifications: Expertise in machine learning and a passion for AR and user experience.
The predicted salary is between 60000 - 80000 £ per year.
Snap is seeking a machine learning expert to develop ML products and AI Lenses that power millions of Snapchatters daily. You will focus on image and video generation, as well as large language models, while building AR experiences with diffusion and flow‑matching models.
You will collaborate with Product, Software Engineering, Lens Content and Data Science teams to prototype ideas, integrate models into production, and refine them through A/B testing and user feedback.
#J-18808-LjbffrGenAI Vision Engineer for Consumer AR (Images & Video) 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 GenAI Vision Engineer for Consumer AR (Images & Video)
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like SNAP!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like GenAI Vision Engineer for Consumer AR (Images & Video) at SNAP.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like SNAP.
✨Apply Directly through Our Website
When you find a suitable opening like GenAI Vision Engineer for Consumer AR (Images & Video) at SNAP, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace GenAI Vision Engineer for Consumer AR (Images & Video)
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!
✨Showcase Your Projects
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.
