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Snap

Lead Machine Learning Engineer, Generative AI (Image & Video)

  • Office
  • 6+ years

Salary

Not stated

Similar roles pay £30K - 155K a year · our estimate

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Description

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 Lead Machine Learning Engineer to join the Consumer Gen AI Product MLE team at Snap!

As the team’s hands-on technical lead, you’ll set direction, build alongside engineers, and turn advances in generative AI into creative experiences for millions of Snapchatters.

Responsibilities

  • Lead the development of ML-powered products and AI Lenses, focusing on image and video generation and editing, as well as LLM-powered experiences
  • Define the team’s technical roadmap and architecture for GenAI pipelines, including diffusion and flow matching models. Balance visual quality, latency, reliability, and cost
  • Drive complex projects from prototype to production. Turn ambiguous ideas into clear technical plans, guide execution, and stay hands-on to ship initial consumer-facing experiences within weeks
  • Partner with Product, Software Engineering, Lens Content, and Data Science to shape ideas, align priorities, and improve experiences through A/B testing and user feedback
  • Turn emerging research into practical improvements. Evaluate open-source models and third-party APIs, establish quality benchmarks, and lead build-versus-buy decisions
  • Mentor and unblock engineers through hands-on collaboration, technical design, and code reviews. Build reusable capabilities that help the team deliver better products, faster
  • Knowledge, Skills & Abilities:
  • A passion for machine learning, with the curiosity to explore new research and the judgment to know what is worth building
  • Deep understanding of mathematics, deep learning, and generative modeling
  • Ability to set technical direction and lead complex initiatives through ambiguity
  • Excellent communication skills, with the ability to explain trade-offs, align partners, and help other engineers grow
  • Strong product judgment and meticulous attention to visual quality
  • Minimum Qualifications:
  • Strong background in Machine Learning, with experience developing generative models, computer vision systems, or related deep learning applications
  • Strong programming skills in Python or C++, with proficiency in PyTorch or a comparable deep learning framework
  • Bachelor’s degree in computer science, mathematics, statistics, or a related technical field, or equivalent practical experience
  • At least 5 years of ML experience after a bachelor’s degree, 4 years after a relevant master’s degree, or 1 year after a relevant PhD
  • Demonstrated experience leading complex ML projects into production, including architecture decisions, guiding other engineers, and cross-functional delivery
  • Preferred Qualifications:
  • 7+ years of experience developing and deploying machine learning systems, with a track record of hands-on technical leadership
  • Experience shipping consumer-facing products for image or video generation and editing
  • Hands-on experience with diffusion or flow matching models, including fine-tuning, conditioning, or inference optimization
  • Experience evaluating visual quality, prompt adherence, identity preservation, or temporal consistency
  • Knowledge of computer graphics, augmented reality, or multimodal models for creative applications
  • A track record of translating research into successful GenAI products
  • 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!

Where you’d work

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About the company

Snap

Office in London, United Kingdom

Also hiring in Toronto, Canada, Los Angeles, United States, New York, United States and 14 more places

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  • Must-haves
Details11 facts · Role, Location, Compensation, Employment
Tech stack
  • Python
  • PyTorch
  • LLMs
  • Computer vision
Seniority
Lead
Type
Full-time
Specialty
ML
Region
United Kingdom
Pay period
Annual
Show 5 more factsShow less

Role

Category
Data & Analytics
Specialty
ML
Seniority
Lead
Experience
5+ years
Tech stack
  • Python
  • PyTorch
  • LLMs
  • Computer vision

Location

Work model
Office
Region
United Kingdom
Office
  • London, United Kingdom

Compensation

Salary
Salary by agreement
Pay period
Annual

Employment

Type
Full-time

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