On-siteFull Time$229k - $343k per yearPosted 3 days ago
About the role
We’re looking for a Machine Learning Engineering Manager to join the Advertiser Experience ML team at Snap!
Advertiser Experience ML is a horizontal Machine Learning and AI team within Ads Platform that builds the intelligence layer behind advertiser-facing products and platform safety. We transform creative, web, app, and advertiser signals into production-grade ML and agentic systems that power ad moderation, fraud detection, advertiser understanding, recommendations, ranking, attribution, creative intelligence, and creator insights
Our work spans applied ML, large-scale data and inference pipelines, LLM-powered workflows, and reliable ML/AI platform infrastructure
Lead a team of machine learning engineers and software engineers building the models, agentic systems, and data pipelines behind ad review, fraud detection, advertiser recommendations, creative intelligence, and web and app understanding
Set the team’s technical strategy and own its roadmap, making prioritization calls across the product and platform teams that depend on its signals
Scale LLM-powered and agentic ad review so more moderation decisions are automated without lowering precision or policy quality
Partner with Product, Data Science, Business Integrity, Ranking, Attribution, and Recommendations teams to define success metrics, align roadmaps, and deliver measurable outcomes
Maintain deep technical involvement in the team’s work, from design and launch decisions to hands-on contributions when priorities require it
Hire, develop, and retain a high-performing team, and hold a high bar for model quality, reliability, cost, privacy, and responsible AI 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
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
Lactation rooms (based on office location) and breastmilk shipping coverage
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
12 paid holidays per year
15 sick and safe days per year
Speaker series, classes, and subscriptions to educational programs
Meditation and yoga classes
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!
Track record of setting a team strategy and turning it into a roadmap that delivered business results
Technical depth to guide design decisions across modeling, data pipelines, and inference
Experience building production systems with large language models, including evaluation, iteration, and managing cost and latency
Deep understanding of machine learning approaches and their application to classification, recommendation, and content understanding problems
Management and mentorship skills
Experience managing cross-functional stakeholders with competing priorities
1+ years of experience leading machine learning engineering teams
Bachelor’s in a related technical field such as computer science or equivalent years of experience
8+ years of post-Bachelor’s ML industry experience; or a Master’s degree in a technical field + 7+ year of post-grad ML experience; or a PhD in a related technical field + 4+ years of post-grad ML experience
Experience in ads integrity, content moderation, or trust and safety
Experience with fraud, risk, or abuse detection
Experience with ads or marketplace recommendation systems
Experience building agentic systems or LLM-based workflows in production
Experience with large-scale web crawling or URL and content understanding
Experience with multimodal models across image, video, and text
Experience with ML platform infrastructure such as distributed batch processing, workflow orchestration, and observability
Experience with frameworks such as PyTorch or TensorFlow