Software Engineer, ML Infrastructure, Level 5

Location: Bellevue, India | Los Angeles, Canada | 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 empower people to express themselves, live in the moment, learn about the world, and have fun together through Snapchat, Lens Studio, and Spectacles. Our Engineering teams build fun and technically sophisticated products that reach hundreds of millions of Snapchatters daily, with a deep commitment to privacy, precision, and our creative culture. As a Software Engineer, ML Infrastructure (Level 5) in Engineering, you’ll play a critical role in scaling our ML infrastructure, optimizing AI training and inference systems, and driving innovations that power Snapchat’s real-time AR Lenses, personalized recommendations, and camera-first experiences. You’ll design and optimize infrastructure for machine learning workloads at massive scale, develop high-performance inference systems for fast AI model serving, and build scalable training, evaluation, and data management pipelines in the cloud. Working on state-of-the-art vector search algorithms, you’ll enhance the precision and scalability of retrieval systems that make Snapchat’s feeds and discoveries magical. Collaborating with ML engineers, you’ll deploy cutting-edge models into production, ensuring efficiency and reliability for AR innovations in Lens Studio and Spectacles, all while upholding our privacy-first values. We’re looking for engineers with strong programming skills, distributed systems expertise, and a passion for big data frameworks like Spark or Ray. Join our fast-moving, creative culture where diverse voices drive human progress through camera technology and AR. Snap practices a 'Default Together' policy, expecting 4+ days per week in office to build our culture faster. We’re proud to be an equal opportunity employer, offering competitive pay (Zone A: $209,000-$313,000 base; equity eligible), comprehensive benefits, and accommodations for disabilities.

What You'll Do

• Design and optimize infrastructure systems for machine learning workloads at scale, driving reliability and efficiency improvements across Snapchat’s ML Infrastructure
• Develop high-performance inference systems to ensure fast and efficient AI model serving for real-time AR experiences
• Build infrastructure to perform scalable ML model training, evaluation, and inference in the cloud
• Create comprehensive data management systems for scalable data collection, labeling, processing, and evaluation
• Work on state-of-the-art vector search algorithms to improve precision, recall, and scalability of retrieval systems powering Snapchat recommendations
• Collaborate closely with ML engineers to deploy cutting-edge models into production for camera-based features and Lenses
• Optimize AI training and inference systems to support Snapchat’s ranking and recommendation engines at massive scale
• Drive innovations that enhance AR innovations in Lens Studio and Spectacles
• Ensure privacy and precision in all ML infrastructure to protect Snapchatters' data
• Scale systems to reach hundreds of millions of daily Snapchatters

Minimum Qualifications

• Bachelor’s degree in a technical field such as computer science or equivalent practical experience
• 6+ years of post-Bachelor’s software development experience; or Master’s degree in a technical field + 5+ years of post-grad software development experience; or PhD in a relevant technical field + 2+ years of post-grad software development experience
• Experience building large-scale production machine learning systems, distributed systems, or big data processing
• Strong programming skills in Python, Java, Scala, or C++
• Good understanding of distributed systems and infrastructure components of large-scale ML
• Experience with big data processing frameworks such as Spark, Flink, or Ray
• Proven track record of operating highly-available systems at significant scale

Preferred Qualifications

• Master’s or PhD in a technical field such as computer science or equivalent industry experience
• Experience working with ML training platforms or optimizing AI model inference
• Familiarity with ML frameworks such as TensorFlow, PyTorch, Caffe2, Spark ML, scikit-learn, or related frameworks

Knowledge, Skills & Abilities

• Strong programming in Python, Java, Scala, or C++
• Problem-solving with focus on system performance, scalability, and efficiency
• Understanding of distributed systems and large-scale ML infrastructure
• Experience with big data frameworks like Spark, Flink, or Ray
• Building high-performance inference and training systems
• Vector search algorithms and retrieval optimization
• Data management for collection, labeling, and processing
• Collaboration with ML engineers for production deployment
• Operating highly-available systems at scale
• Proactive learning of new concepts
• Privacy-focused engineering practices
• Cloud-based ML infrastructure development
• AR and camera technology integration knowledge
• Team collaboration and communication

Our Benefits

• Paid parental leave
• Comprehensive medical coverage
• Emotional and mental health support programs
• Compensation packages that let you share in Snap’s long-term success through equity (RSUs)
• Office collaboration under our 'Default Together' policy (4+ days per week in office)
• Support for disabilities or special needs with accommodations
• Diverse and inclusive culture fostering innovative products
• Global community well-being initiatives rooted in Snap values

Compensation

$209,000-$313,000 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.