Manager of Software Engineering, Snap Inc.

• Bachelor's degree in a technical field such as computer science or equivalent years of experience
• 9+ years of post-Bachelor's software engineering experience; or a Master's degree in a technical field + 8+ years of post-grad experience; or a PhD in a related technical field + 5+ years of post-grad experience
• 1+ year(s) of experience managing an engineering team
• Experience with distributed systems and large-scale ML infrastructure
• Strong understanding of ML infrastructure systems including model training platforms, inference serving, feature stores, and data pipelines
• Background building high availability, mission-critical systems at significant scale
• Experience setting technical direction for teams whose work directly enables ML engineers and production ML systems
• Strong management and mentorship skills, with the ability to lead and grow senior engineers
• Excellent verbal and written communication skills, with high attention to detail
• Ability to collaborate with internal and external stakeholders at all levels
• Skilled at managing ambiguous problems and driving clarity across complex, multi-team initiatives
• Proficiency in, or a strong aptitude for, leveraging AI tools to streamline development, paired with the critical judgment to audit generated output for architectural integrity, performance bottlenecks, and security risks
• Adaptability in learning and applying evolving AI systems and tools to remain at the forefront of engineering trends and modern development practices

Desirable

• We're looking for a Manager, Software Engineering, ML Inference to join Snap Inc.!
• Lead and mentor a team of ML Infrastructure engineers responsible for building and scaling the systems that power Snap's model training, inference, and data pipelines
• Set the strategy, build a roadmap, create measurable goals, and lead your team to deliver high-impact ML infrastructure initiatives
• Evaluate the technical tradeoffs of key decisions and serve as a strong technical mentor across the team
• Perform design and code reviews to continuously raise the technical excellence bar
• Collaborate with ML engineers, product teams, and cross-functional stakeholders to understand requirements, evaluate tradeoffs, and deliver solutions at scale
• Hire, grow, and retain high-performing engineers by creating growth opportunities, giving regular feedback, and managing performance
• Advocate for and apply best practices when it comes to availability, scalability, operational excellence, and cost management
• 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