Software Engineer, ML Infrastructure, ML Platform Level 5

Snap•Santa Monica, CA

6d•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 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, model orchestration, and model data quality. The role focuses on designing, building, and optimizing infrastructure for large-scale machine learning workloads. This includes feature generation and serving pipelines, cloud-based model training and evaluation, high-performance inference, and data management systems. The engineer will work closely with ML engineers to put advanced models into production and use AI tools and high-velocity engineering workflows while maintaining strong standards for correctness, security, and production quality. Snap follows a “default together” approach and expects team members to work in an office at least four days per week. The position offers equity in the form of RSUs. U.S. base salary ranges vary by pay zone: Zone A (CA, WA, NYC), $209,000–$313,000 annually; Zone B, $199,000–$297,000 annually; and Zone C, $178,000–$266,000 annually. 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 the infrastructure components of large-scale machine learning.
Experience with big data processing frameworks such as Spark, Flink, or Ray.
Ability to collaborate and work well with others.
Proven 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, tools, and modern development practices.
Bachelor’s degree in a technical field such as computer science, or equivalent experience, plus 6+ years of post-bachelor’s software development experience; or a master’s degree in a technical field plus 5+ years of post-graduate software development experience; or a PhD in a relevant technical field plus 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 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.

Responsibilities

Design and optimize infrastructure systems for machine learning workloads at scale, and improve reliability and efficiency across Snapchat’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 closely 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 standards for code correctness, security, and production-ready quality.