Software Engineer, ML Infrastructure, ML Platform Level 5

Snap Inc.•Los Angeles, CA

3d•$178,000 - $313,000•Onsite

About The Position

Snap Inc. is seeking a Software Engineer to join the ML Platform Experience team within its core ML Platform organization. The team builds agentic experiences for building, managing, and operating foundational models at Snapchat. It uses Python as its primary language, with Java and Go as supporting languages, and builds agents using ADK, Langfuse, and frontier large language models. The team also works on foundational technologies including model lineage, model orchestration, and model data quality. The role focuses on designing and improving machine-learning infrastructure and systems at scale. This includes feature generation and serving pipelines, model training and evaluation infrastructure, high-performance inference, and data management. The engineer will work closely with ML engineers to bring models into production and use AI tools and high-velocity engineering workflows while maintaining standards for correctness, security, and production quality. Snap follows a “default together” approach and expects team members to work in an office four or more days per week. The position is eligible for RSU equity. U.S. base salary ranges are $209,000–$313,000 for Zone A (CA, WA, NYC), $199,000–$297,000 for Zone B, and $178,000–$266,000 for 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.
Proven track record 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.
At least 6 years of post-Bachelor’s software development experience; or a technical Master’s degree and at least 5 years of post-graduate software development experience; or a relevant technical PhD and at least 2 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 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.

Responsibilities

Design and optimize infrastructure systems for machine-learning workloads at scale, and improve 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 and 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 rigorous standards for code correctness, security, and production-ready quality.