Staff Machine Learning Engineer, Level 6

Location: Bellevue, India | Palo Alto, Canada | Santa Monica, United States

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 represents the greatest opportunity to improve the way people live and communicate. We're building the next generation of AR experiences through Snapchat, Lens Studio, and Spectacles, empowering people to express themselves, live in the moment, and have fun together. Our Engineering teams create technically sophisticated products reaching hundreds of millions of Snapchatters daily, always prioritizing privacy, speed, and creativity. Join us as a Staff Machine Learning Engineer (Level 6) in Engineering to drive AR innovation and personalized camera experiences that redefine social interaction. In this role, you'll lead the development of state-of-the-art ML models that enhance Snapchat's core features, from real-time AR Lenses and image generation to personalized recommendations and content understanding. You'll architect scalable systems that power advertiser value and user delight, evaluating tradeoffs to deliver robust products at Snap's blistering pace. Collaborate with AR creators, product teams, and external partners to tackle ambiguous challenges in computer vision and generative AI, ensuring every model aligns with our creative culture and privacy-first values. We're seeking a technical leader with deep ML expertise who thrives in a dynamic environment. You'll mentor peers, conduct code reviews, and iterate rapidly on production ML pipelines optimized for camera and AR workloads. At Snap, our 'default together' policy fosters in-person collaboration 4+ days a week to accelerate culture and innovation. If you're passionate about pushing the boundaries of AR through machine learning, apply to help shape the future of visual communication.

What You'll Do

• Create advanced ML models that power personalized experiences on Snapchat, enhancing user engagement through camera and AR features
• Develop models for content understanding, image generation, and recommendations tailored to Snapchat's visual messaging and Lens Studio ecosystem
• Evaluate technical tradeoffs in ML systems to balance innovation speed with scalability for hundreds of millions of daily users
• Perform code reviews and mentor engineers to maintain exceptional code quality in AR and camera ML pipelines
• Build robust, scalable ML infrastructure that supports real-time AR Lenses and Spectacles integrations
• Iterate quickly on models to drive value for users, advertisers, and Snap's creative AR initiatives
• Collaborate with cross-functional teams including AR designers and product managers to solve ambiguous problems in camera technology
• Optimize ML models for privacy-preserving inference on edge devices like Spectacles
• Experiment with cutting-edge techniques in generative AI for AR content creation
• Drive technical leadership in ML projects that advance Snap's mission to empower self-expression through the camera

Minimum Qualifications

• Bachelor's Degree in a relevant technical field such as computer science or equivalent years of practical work experience
• 8+ years of post-Bachelor’s machine learning experience; or Master’s degree in a technical field + 7+ years of post-grad machine learning experience; or PhD in a relevant technical field + 4 years of post-grad machine learning experience
• Experience developing machine learning models for ranking, recommendations, search, content understanding, image generation, or other relevant applications of machine learning
• Strong understanding of machine learning approaches and algorithms
• Experience working with large-scale data systems and real-time ML inference
• Ability to evaluate technical tradeoffs and ensure code quality through reviews
• Proven track record of building scalable ML products in production environments

Preferred Qualifications

• Advanced degree in computer science or related field
• Experience with machine learning frameworks such as TensorFlow, PyTorch, Caffe2, Spark ML, or scikit-learn
• Experience with ML for AR, computer vision, or camera-based applications
• Background in ranking infrastructures, recommendation systems, or AR content generation
• Experience designing ML systems for high-traffic consumer apps

Knowledge, Skills & Abilities

• Deep expertise in machine learning algorithms and deep learning architectures
• Proficiency in Python and ML frameworks (TensorFlow, PyTorch, etc.)
• Experience with computer vision and image processing for camera technologies
• Strong skills in model evaluation, A/B testing, and experimentation
• Ability to design scalable ML systems for high-volume, real-time applications
• Expertise in recommendation systems, ranking, or generative models
• Solid understanding of data pipelines, Spark, and big data technologies
• Technical leadership and mentorship capabilities
• Problem-solving in ambiguous, fast-paced environments
• Collaboration with cross-functional teams (product, design, AR)
• Prioritization and independent execution skills
• Knowledge of privacy-focused ML practices
• Experience with AR/ML integration (e.g., Lens Studio, Spectacles)
• Code review and ensuring production-grade quality
• Rapid iteration without compromising reliability

Our Benefits

• Paid parental leave
• Comprehensive medical, dental, and vision coverage
• Emotional and mental health support programs
• Competitive compensation packages with equity in the form of RSUs
• Flexible paid time off and wellness stipends
• Professional development opportunities and learning budgets
• Onsite perks including meals, fitness facilities, and creative workspaces
• 401(k) matching and financial planning resources

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.