Principal Machine Learning Engineer, Signals and Measurement

SNAP/SNAP

. Design and develop machine learning systems across the third-party signal lifecycle, from acquisition and curation to matching, attribution, and causal measurement .

Posted 9/30/2026full-timeUnited StatesLead💰 $276,000 - $414,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing, developing, and optimizing machine learning models, particularly for recommendation and ranking use cases, while collaborating effectively across teams and advocating for best practices in operational excellence and scalability.

Highest-signal resume keywords

Machine Learning ExperienceDeep Learning ApproachesTensorFlowPyTorchOnline Advertising

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningDeep LearningModel OptimizationProgramming SkillsSoftware DesignRecommendation SystemsRanking ModelsCausal MeasurementAnomaly DetectionAttribution Methodologies

Soft Skills

CollaborationMentorshipProblem SolvingLeadershipCommunication

Tools & Technologies

TensorFlowPyTorchMeasurement StackIdentity ResolutionAd Targeting

Industry Keywords

Machine LearningOnline AdvertisingRecommendationRankingMarketplace Optimization

Tech Stack

Tools & technologies

PyTorchTensorflow

About the role

Key responsibilities & impact

Design and develop machine learning systems across the third-party signal lifecycle, from acquisition and curation to matching, attribution, and causal measurement
Design, implement, and scale critical machine learning models to support Snap's monetization strategies
Collaborate with cross-functional teams to set and align on machine learning strategies to meet company objectives
Stay up-to-date with the latest machine learning technology and apply it to complex problems
Collaborate with leadership to improve the ML tech stack and organizational performance
Work across teams to understand product requirements, evaluate trade-offs, and deliver solutions for innovative products or services
Advocate for best practices in availability, scalability, operational excellence, and cost management
Provide technical direction that influences the entire ML community

Requirements

What you’ll need

Bachelor's in a technical field such as computer science, mathematics, statistics or equivalent years of experience
11+ years of industry machine learning experience
Strong understanding of machine learning and deep learning approaches and algorithms, including applications to advertising measurement, recommendation, and/or search
Experience setting the direction for a team whose primary output is online ranking/recommendation models
Experience developing and shipping performant and scalable machine learning models for recommendation or ranking use cases
Ability to design, train, and optimize advanced machine learning models
Excellent programming and software design skills
Experience with TensorFlow, PyTorch, or related deep learning frameworks
Experience with signals and measurement stack, identity resolution, anomaly detection or causal measurement
Familiarity with attribution and advanced measurement methodologies
Experience in online advertising, including ad targeting, ranking, auction, and/or marketplace optimization
Advanced degree in a related field such as machine learning, computer vision, or mathematics
Experience partnering with cross-functional executives and management across a globally distributed organization
Track record of delivery in rapidly changing, highly collaborative, multi-site, multi-stakeholder environments
Experience working with a diverse group of engineers
Experience contributing to AI publications
Ability to proactively learn new concepts and technology
Skilled at solving ambiguous problems and leading and executing complex technical initiatives
Strong collaboration and mentorship skills

Benefits

Comp & perks

Paid parental leave
Comprehensive medical coverage
Emotional and mental health support programs
Compensation packages including equity in the form of RSUs
Default Together policy with in-office work 4+ days per week