Software Engineer, Snap Inc.

• Strong programming skills in Python, Java
• Strong problem-solving skills with a focus on system performance, scalability, and efficiency
• Good understanding of distributed systems and the infrastructure components of 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 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 to remain at the forefront of engineering trends and modern development practices
• Bachelor’s degree in a technical field such as computer science or equivalent experience
• 6+ years of post-Bachelor’s software development experience; or Master’s degree in a technical field + 5+ year 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

Desirable

• We’re looking for a Software Engineer to join the ML Platform Experience team, part of the core ML Platform organization. We are an AI native team which builds the agentic user experience for building, managing, and operating foundational models at Snapchat
• We utilize Python as the primary language with Java/Go as supporting languages, we build agents on ADK, langfuse, and frontier LLM models, and are responsible for many other foundational technology such as model lineage, model orchestration, model data quality, and more
• Design and optimize infrastructure systems for machine learning workloads at scale and drive reliability and efficiency improvements across Snapchat’s ML Infrastructure
• Build and enhance feature generation and serving pipelines that power online inferencing and offline training data generation
• Develop high-performance inference systems to ensure fast and efficient AI model serving
• Build infrastructure to perform scalable ML model training, evaluation, and inference in the cloud
• Build comprehensive data management systems for scalable data collection, labeling, processing, and evaluation
• Work closely with ML engineers to deploy cutting-edge models into production
• Utilize AI tools and high velocity engineering workflows to design and ship scalable services while upholding rigorous standards for code correctness, security, and production ready quality code