Software Engineer, ML Infrastructure

Location: London, United Kingdom

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 our core products: Snapchat, a visual messaging app; Lens Studio, an augmented reality 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 us as a Software Engineer, ML Infrastructure to scale our ML systems, optimizing AI training and inference for Snapchat’s innovative ranking, recommendation, and AR features that make camera technology magical and creative. In this role, you’ll design and optimize infrastructure for machine learning workloads at massive scale, building feature pipelines, high-performance inference systems, and data management solutions that power real-time and batch models. You’ll collaborate with ML engineers to deploy cutting-edge models into production, enhancing Snapchat’s personalized content recommendations, Lens Studio AR experiences, and Spectacles innovations. Your work will drive efficiency and reliability, ensuring Snapchatters enjoy seamless, fun interactions powered by efficient AI that leverages our camera-first approach to creativity and connection. We’re looking for engineers with strong programming skills, distributed systems expertise, and a passion for big data frameworks like Spark or Ray. If you thrive in a fast-paced, collaborative environment with a proven track record in large-scale ML systems, you’ll fit right into our creative culture. Snap is proud to be an equal opportunity employer, committed to diverse backgrounds driving innovative products. Our “Default Together” policy means working in-office 4+ days a week to build culture faster. With comprehensive benefits like paid parental leave, medical coverage, and mental health support, we’ve got your back to innovate boldly.

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
• Build and enhance feature generation pipelines that power real-time and batch ML models for content ranking and recommendations
• Develop high-performance inference systems to ensure fast and efficient AI model serving for Snapchat's AR experiences and camera features
• 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 closely with ML engineers to deploy cutting-edge models into production, enhancing Snapchat's visual messaging and Lens Studio AR capabilities
• Optimize AI systems to support innovative camera technologies and real-time AR innovations on Snapchat
• Collaborate with cross-functional teams to scale ML infrastructure that powers personalized recommendations and ranking for hundreds of millions of Snapchatters
• Drive innovations in ML infrastructure to improve efficiency and impact of Snapchat’s creative, fun, and immersive user experiences
• Ensure privacy and precision in all ML systems, aligning with Snap's core values

Minimum Qualifications

• Bachelor’s degree in a technical field such as computer science or equivalent practical experience
• Post-Bachelor’s software development experience, or Master’s degree in a technical field plus post-grad software development experience, or PhD in a relevant technical field
• 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++
• Expertise in system performance, scalability, and efficiency
• Deep knowledge of distributed systems
• Experience with large-scale ML infrastructure
• Proficiency in big data frameworks like Spark, Flink, or Ray
• Strong problem-solving skills
• Ability to collaborate effectively with ML engineers and cross-functional teams
• Proven operation of highly-available systems at scale
• Skill in building feature generation pipelines
• Expertise in high-performance inference systems
• Knowledge of scalable ML training and evaluation
• Data management for collection, labeling, and processing
• Proactive learning and application of new concepts
• Focus on privacy and precision in engineering
• Understanding of cloud-based ML infrastructure

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
• Support for disabilities or special needs requiring accommodation
• “Default Together” policy fostering dynamic in-person collaboration 4+ days per week
• Opportunities to contribute to a creative culture building fun AR and camera innovations
• Global community commitment with focus on well-being and diverse voices

"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.