Machine Learning Engineer (Generative ML)

• Snap’s Generative ML Platform team builds cutting-edge AI technologies that power creative, scalable experiences for hundreds of millions of Snapchatters worldwide.
• From multimodal LLMs and video generation to real-time AR, human understanding, and 3D content creation, we develop the full stack of generative AI, including foundational models, efficient infrastructure, and on-device and server-side inference.
• Our team creates intuitive tools, platforms, and agentic systems that empower creators, developers, and internal teams to bring ideas to life, while advancing personalized, human-centric experiences across mobile, web, and wearable devices like Spectacles
• Develop innovative machine learning technology and products that serve millions of Snapchatters
• Work on state of the art generative pipelines for image, video, language or audio generation
• Deliver generative machine learning experiences on device
• Build cutting-edge augmented reality experiences using generative and diffusion models
• Partner with cross-functional Snap teams to explore and prototype new products

Benefits

• Up to 28 weeks of parental leave and return-to-work program
• Adoption, surrogacy, infertility, and fertility preservation benefits
• Backup child care coverage, center-based care support, & caregiver assistance
• Dependent Daycare Flexible Spending Account
• Services to support your path to parenthood & beyond - fertility support & family planning via Carrot, SNOO, Hinge Health
• Short-term disability, long-term disability, basic life insurance, and AD&D insurance
• Lactation rooms (based on office location) and breastmilk shipping coverage
• For Snap, employees taking care of loved ones with complex, chronic, or ongoing care needs (i.e. parent with Dementia, spouse with Cancer, child with Autism), your family can save time, money, & stress with Wellthy
• Comprehensive medical coverage, including PPO, HDHP with HSA, and HMO options
• Dental coverage, including orthodontia benefits
• Vision coverage, including frame and contact allowance and LASIK benefits
• Free membership to One Medical for primary and urgent healthcare services
• Business Travel Insurance
• Gym perks and discounts
• Team fitness classes and races
• Sports leagues
• Cooking and nutritional workshops
• Well-being reimbursement
• Unlimited access to virtual physical therapy with Anthem
• 15 sessions per year of mental health for you + dependents through Lyra
• Generous time off and leave programs. In the US, this includes the following:
• Up to 3 weeks (120 hours) of vacation time and 1 floating holiday for non-exempt team members
• 15 sick and safe days per year
• 12 paid holidays per year
• Meditation and yoga classes
• Speaker series, classes, and subscriptions to educational programs
• Social gatherings, team outings, and volunteering programs
• Snap Inc. provides a 401(k) plan that allows you to save on a pre-tax, Roth, and after-tax basis for your retirement (yes, we even have the Mega backdoor option!) Snap will also match 100% up to 3% of your contribution and then 50% on your 4th and 5th%
• Flexible Spending Accounts for healthcare, daycare and commuter
• Health Savings Account with employer contributions
• Rocket Lawyer memberships
• Financial education programs
• Snap exclusive discounts and perks
• Compensation packages that let you share in Snap’s long-term success!

Preferred experience

• Desire to solve open ambiguous problems
• Knowledge of mathematics and deep learning foundations
• Desire to grow professionally, learn and help others
• Proficiency working with major deep learning frameworks: PyTorch or TensorFlow
• A proven passion for machine learning; you stay up-to-date with research and are excited about prototyping new ideas quickly
• Ability to effectively collaborate with internal teams and external partners
• Ability to work independently
• Strong software development skills in Python or C++
• Bachelor’s Degree in a technical field such as computer science, mathematics, statistics or equivalent years of experience
• Research or engineering experience in one or more of the following: generative models, efficient models, diffusion models, language models, or other related applications of machine learning
• 5+ years of post-Bachelor’s machine learning experience; or Master’s degree in a technical field + 4+ year of post-grad machine learning experience; or PhD in a relevant technical field + 1 years of post-grad machine learning experience
• Master’s degree or PhD in a related technical field
• Knowledge of GenAI, especially image, video, language and audio generation foundations
• Experience developing real-time software for mobile applications
• Track record of successful projects in GenAI field
• Knowledge of efficient model foundations
• Examples of your work such as open source projects, blog posts, Kaggle contests, top conference or journal publications, etc