Manager, Machine Learning Engineering, Content Ranking

Location: Bellevue, India | Los Angeles, Canada | New York, United States | Palo Alto, Canada | San Francisco, Canada | Seattle, India

Department: Engineering

Employment Type: Full time

About Snap Inc

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.

About the Role

Snap Inc is a camera company that believes the camera presents the greatest opportunity to improve the way people live and communicate. We contribute to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together through our core products: Snapchat, a visual messaging app; Lens Studio, an AR platform; and Spectacles, our AR glasses. Snap Engineering teams build fun and technically sophisticated products reaching hundreds of millions of Snapchatters daily. We're deeply committed to our global community's well-being, moving fast with precision and privacy at the forefront. Join our Content Ranking team as a Manager, Machine Learning Engineering, to power personalized video recommendations that enhance creative, camera-driven experiences on Snapchat. In this role, you'll lead a team of ML and software engineers to develop and optimize our recommendation engine, defining scalable architectures that integrate AR innovations and real-time personalization. You'll drive rapid iterations, collaborate with infrastructure teams on robust ML systems, and evaluate tradeoffs through A/B testing to boost engagement with Snapchat's ephemeral content. By performing code reviews and fostering technical excellence, you'll ensure our systems reliably surface the most relevant Lenses, Stories, and videos, all while championing Snap's creative culture and privacy standards. We're seeking a leader with deep ML expertise in recommender systems, proven team management, and the ability to thrive in ambiguity. If you have experience with real-time ranking, large-scale frameworks like PyTorch or TensorFlow, and a passion for AR-driven innovation, you'll excel in Snap's fast-paced environment. We practice a 'Default Together' policy (4+ days/week in office) to build culture through collaboration. Snap is an equal opportunity employer committed to diversity, offering comprehensive benefits including equity, medical coverage, parental leave, and mental health support.

What You'll Do

• Lead a team of machine learning engineers and software engineers in developing and optimizing Snap's personalized video recommendation engine for Snapchat content
• Define the overall architecture of the content recommender system, ensuring scalability, performance, and reliability to deliver engaging AR experiences
• Drive rapid iteration without compromising quality, integrating camera-based features and real-time personalization
• Work closely with infrastructure engineers to build robust machine learning infrastructure supporting the recommender system
• Evaluate technical tradeoffs in key decision-making processes to ensure optimal outcomes for Snap's creative content ecosystem
• Conduct A/B testing and analyze performance metrics to continuously improve recommendation quality and user engagement
• Perform design and code reviews to raise the technical excellence bar across the Content Ranking team
• Collaborate with product, design, and AR teams to innovate on camera-driven content discovery and ranking
• Mentor engineers in applying ML to enhance Snapchat's visual messaging and Lens Studio integrations
• Champion privacy and ethical AI practices in all recommendation systems, aligning with Snap's core values

Minimum Qualifications

• Bachelor’s degree in a related technical field such as computer science or equivalent practical experience
• 8+ years of post-Bachelor’s ML industry experience; or a Master’s degree in a technical field + 7+ years of post-grad ML experience; or a PhD in a related technical field + 4+ years of post-grad ML experience
• 1+ year(s) of experience leading machine learning teams focused on ranking and/or recommendations
• Deep understanding of machine learning approaches, algorithms, and their application to recommender systems
• Experience setting the direction for teams developing online ranking and recommendation models
• Strong management and mentorship skills, fostering a collaborative and innovative team culture
• Excellent verbal and written communication skills with meticulous attention to detail

Preferred Qualifications

• Experience with real-time recommendation systems
• Experience working with large-scale machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks
• Experience working with distributed systems
• Experience working with machine learning, ranking infrastructures, and system designs
• Ability to proactively learn new concepts and apply them at work

Knowledge, Skills & Abilities

• Machine learning algorithms and recommender systems
• Online ranking and recommendation models
• Team leadership and mentorship
• Technical architecture design for scalability
• A/B testing and performance metrics analysis
• Code and design review processes
• Stakeholder collaboration across levels
• Problem-solving in ambiguous environments
• Verbal and written communication
• Attention to detail
• Real-time systems experience
• Large-scale ML frameworks (TensorFlow, PyTorch, etc.)
• Distributed systems
• ML infrastructure and system design
• Privacy-focused engineering
• AR and camera technology integration
• Rapid iteration in agile environments

Our Benefits

• Paid parental leave
• Comprehensive medical coverage
• Emotional and mental health support programs
• Compensation packages with equity in the form of RSUs
• Competitive base salary based on pay zones (Zone A: $229,000-$343,000; Zone B: $218,000-$326,000; Zone C: $195,000-$292,000)
• "Default Together" policy with 4+ days per week in office to foster dynamic collaboration
• Opportunities to contribute to innovative AR products like Snapchat and Spectacles
• Support for diverse backgrounds in a creative, fast-paced culture

Compensation

$229,000-$343,000 annually

This position is eligible for equity in the form of RSUs.

"Default Together" Policy: At Snap Inc, we practice a "default together" approach and expect team members to work in an office 4+ days per week.

Snap is proud to be an equal opportunity employer.