Software Engineer, ML Infrastructure, ML Platform Level 5

Snap Inc.•Los Angeles, CA

1d•$178,000 - $313,000•Onsite

About The Position

Snap Inc. is hiring a Software Engineer to join its ML Platform Experience team within the core ML Platform organization. The AI-native team builds agentic experiences for building, managing, and operating foundational models at Snapchat. It primarily uses Python, with Java and Go as supporting languages, and builds agents using ADK, Langfuse, and frontier LLM models. The team also works on foundational technologies including model lineage, orchestration, and data quality. The role focuses on designing, building, and operating large-scale machine-learning infrastructure and systems for training, evaluation, and inference. The engineer will develop feature-generation and serving pipelines, high-performance model-serving systems, and data-management infrastructure, while collaborating with ML engineers to bring models into production. The role also uses AI tools and high-velocity engineering workflows while maintaining strong standards for correctness, security, and production quality. Snap follows a “default together” approach, and team members are expected to work in an office four or more days per week. The position is eligible for RSUs. U.S. base salary ranges are $209,000–$313,000 in Zone A (CA, WA, NYC), $199,000–$297,000 in Zone B, and $178,000–$266,000 in Zone C. Starting pay depends on job-related skills, experience, qualifications, work location, and market conditions.

Requirements

Strong programming skills in Python and Java.
Strong problem-solving skills focused on system performance, scalability, and efficiency.
Good understanding of distributed systems and infrastructure components for large-scale ML.
Experience with big-data processing frameworks such as Spark, Flink, or Ray.
Ability to collaborate and work well with others.
Track record of operating highly available systems at significant scale.
Ability to proactively learn new concepts and apply them at work.
Adaptability in learning and applying evolving AI systems and tools.
Bachelor’s degree in a technical field such as computer science, or equivalent experience.
One of the following: 6 or more years of post-bachelor’s software development experience; a master’s degree in a technical field and 5 or more years of post-graduate software development experience; or a PhD in a relevant technical field and 2 or more years of post-graduate software development experience.
Experience building large-scale production machine-learning systems, distributed systems, or big-data processing systems.

Nice To Haves

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 TensorFlow, PyTorch, Caffe2, Spark ML, scikit-learn, or related ML frameworks.

Responsibilities

Design and optimize infrastructure systems for machine-learning workloads at scale, improving reliability and efficiency across Snap’s ML infrastructure.
Build and enhance feature-generation and serving pipelines for online inference and offline training-data generation.
Develop high-performance inference systems for fast, efficient AI model serving.
Build cloud infrastructure for scalable ML model training, evaluation, and inference.
Build data-management systems for scalable data collection, labeling, processing, and evaluation.
Work with ML engineers to deploy cutting-edge models into production.
Use AI tools and high-velocity engineering workflows to design and ship scalable services while maintaining code correctness, security, and production-ready quality.