Machine Learning Engineer - GenAI

Snapchat
London
2 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer - Computer Vision

Machine Learning Engineer (NLP)

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

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's three core products are Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world; Lens Studio, an augmented reality platform that powers AR across Snapchat and other services; and its AR glasses, Spectacles.

We're looking for Machine Learning Engineers to join the Generative ML Platform team at Snap Inc!

What you'll do:

  1. Develop ML-tools and ML-products that serve millions of Snapchatters on a daily basis
  2. Build cutting-edge augmented reality experiences with diffusion/flow matching models and GANs
  3. Deliver GenAI experiences for the edge devices
  4. Work on state of the art GenAI pipelines for image and video generation
  5. Work closely with other Snap teams to introduce, prototype and launch new products

Knowledge, Skills & Abilities:

  1. A proven passion for machine learning; you stay up-to-date with research and are excited about prototyping new ideas quickly
  2. Knowledge of mathematics and deep learning foundations
  3. Ability to effectively collaborate with internal teams and external partners
  4. Ability to work independently

Minimum Qualifications:

  1. Bachelor's Degree in a technical field such as computer science, mathematics, statistics or equivalent years of experience
  2. Proven research or 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
  3. Experience with the major deep learning frameworks: PyTorch or TensorFlow
  4. Strong programming skills in Python or C++

Preferred Qualifications:

  1. Experience developing real-time software for mobile applications
  2. Knowledge of computer graphics foundations
  3. Track record of successful projects in GenAI field
  4. Examples of your work such as open source projects, blog posts, Kaggle contests, top conference or journal publications, etc.

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Careers

Navigating AI Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

The field of Artificial Intelligence (AI) is growing at an astonishing pace, offering a wealth of opportunities for talented professionals. From machine learning engineers and data scientists to natural language processing (NLP) specialists and computer vision experts, the demand for skilled AI practitioners continues to surge in the UK and globally. AI career fairs present a unique opportunity to connect face-to-face with potential employers, discover cutting-edge innovations, and learn more about the rapidly evolving landscape of data-driven technologies. Yet, attending these events can feel overwhelming: dozens of companies, queues of applicants, and only minutes to make a great first impression. In this detailed guide, we’ll walk you through strategies to prepare for AI career fairs, provide you with key questions to ask, highlight examples of relevant UK events, and reveal the critical follow-up tactics that will help you stand out from the crowd. By the end, you’ll be armed with the knowledge and confidence to land your dream role in the ever-growing world of Artificial Intelligence.

Jobs

Common Pitfalls AI Job Seekers Face and How to Avoid Them

The global demand for Artificial Intelligence (AI) specialists continues to rise, with organisations across industries keen to implement machine learning, deep learning, and data-driven insights into their operations. Yet, as the market for AI professionals flourishes, so does the level of competition among candidates. Talented individuals who may otherwise be qualified often stumble on common pitfalls that can hinder their success in securing an AI-related role. These pitfalls can lie in their CV, interview approach, job search strategy, or even their understanding of what AI employers are looking for. This article aims to help job seekers in the UK’s AI sector—whether you’re fresh out of university, transitioning into AI from another field, or looking for a senior-level position—avoid the most common mistakes. We’ll discuss how to stand out in a crowded AI job market by improving your CV, acing interviews, and conducting an effective job search. Read on to discover the typical missteps AI professionals make when seeking employment and learn the strategies to avoid them.

Careers

Career Paths in Artificial Intelligence: From Research to Management – How to Progress from Technical Roles to Leadership and Beyond

Artificial Intelligence (AI) stands at the forefront of technological innovation, shaping everything from healthcare diagnostics to autonomous vehicles and natural language processing. With the UK widely recognised as a growing hub for AI research and development, there has never been a better time to explore a career in artificial intelligence—or to advance your current trajectory within the field. A key question that often arises is: How can professionals move from hands-on technical roles in AI to leadership and management positions? This comprehensive guide will walk you through the evolving career landscape in AI, from entry-level posts to executive roles. We will examine in-demand skills, recommended pathways for professional development, and strategies to help you seamlessly ascend from technical responsibilities to strategic leadership. Whether you’re a recent graduate, a self-taught data whizz, or an experienced machine learning engineer aspiring to lead teams, this article will provide you with practical insights tailored to the UK’s vibrant AI sector.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.