Machine Learning Engineering Manager (Advertiser Experience ML)

SNAP, Inc.; Palo Alto (CA); On-site; USD 240,000 - 320,000; Full time

Benefits offered by this job

Parental leave up to 28 weeks

Medical and dental coverage

401(k) with company match

Wellbeing and family support programs

Wellness benefits and fitness perks

Job summary

Snap Inc. is seeking an experienced Machine Learning Engineering Manager to lead the Advertiser Experience ML team in Palo Alto. You will drive the technical strategy, own the roadmap, and scale LLM-powered ad review and moderation across advertiser-facing products.

You will partner with product, data science, and platform teams to deliver measurable outcomes while mentoring a high‑performing team and ensuring reliability, privacy, and cost efficiency in production systems.

Qualifications

• Track record of setting a team strategy and turning it into a roadmap with measurable business outcomes.
• Technical depth to guide modeling, data pipelines, and inference decisions.
• Experience building production ML systems with LLMs and agentic workflows.

Responsibilities

• Lead a team of ML and software engineers building models and data pipelines behind ads systems.
• Set technical strategy and own roadmap across product and platform dependencies.
• Scale LLM-powered ad review and automate moderation without sacrificing quality.
• Partner with Product, Data Science, and other teams to define success metrics and outcomes.
• Maintain hands‑on involvement when priorities require it and hire/retain top talent.

Skills

Team leadership

Technical depth

Production systems

LLM workflows

Cost & latency management

Cross-functional leadership

Mentorship

Experience leading ML eng teams

Ads integrity

Fraud detection

Content understanding

Multimodal models

PyTorch

TensorFlow

Observability

Data pipelines

Inference pipelines

LLM-based workflows

Education

Bachelor’s in a related technical field

Tools

PyTorch

TensorFlow

Distributed batch processing

Workflow orchestration

Observability

Job description

• 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
• 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
• 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
• 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
• Social gatherings, team outings, and volunteering programs
• Speaker series, classes, and subscriptions to educational programs
• Meditation and yoga classes
• 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