Staff Machine Learning Engineer, Diffusion, Generative Modeling and Inference

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.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.We’re looking for a Machine Learning Engineer to join Snap Inc!What you’ll do:Develop innovative machine learning technology and products that serve millions of SnapchattersBuild cutting-edge augmented reality experiences using generative modelsDeliver generative machine learning experiences on devicePartner with cross-functional Snap teams to explore and prototype new productsKnowledge, Skills & Abilities:A proven passion for machine learning; you stay up-to-date with research and are excited about prototyping new ideas quicklyFamiliarity with Neural Networks and Deep Learning and Generative ModelingDeep understanding of mathematics and/or machine learning algorithmsDesire to solve open ambiguous problemsDesire to grow professionally, learn and help othersAbility to effectively collaborate with internal teams and external partnersAbility to work independentlyMinimum Qualifications:Bachelor's degree in technical field such as computer science, mathematics, statistics or equivalent years of experience8+ years of post-Bachelor’s machine learning or related experience; or a Master’s degree in a technical field + 7+ years of post-grad ML or related experience; or a PhD in a related technical field + 4+ years of post-grad ML or related experienceExperience with Computer Vision or Generative Modeling techniquesExperience working with machine learning frameworks such as TensorFlow, PyTorch, JAX, MLX, scikit-learn, or related frameworksPreferred Qualifications:Advanced degree in computer science or related fieldExperience training large-scale diffusion models for images, videos or 3DKnowledge of distillation, quantization and model compression techniquesKnowledge of GPU, CPU, or NPU optimization techniquesExperience building and optimizing ML inference pipelines Experience working with machine learning frameworks such as TensorFlow, PyTorch, JAX, MLX, scikit-learn, or related frameworksIf 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.We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, where applicable).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!CompensationIn the United States, work locations are assigned a pay zone which determines the salary range for the position. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. The starting pay may be negotiable within the salary range for the position.These pay zones may be modified in the future.Zone A (CA, WA, NYC):The base salary range for this position is $229,000-$343,000 annually.Zone B: The base salary range for this position is $218,000-$326,000 annually.Zone C:The base salary range for this position is $195,000-$292,000 annually.This position is eligible for equity in the form of RSUs.SummaryLocation: Los Angeles, California; Seattle, Washington; Palo Alto, California; New York, New York; Bellevue, WashingtonType: Full time