Staff Software Engineer

• Design and optimize infrastructure systems for machine learning workloads at scale and drive reliability and efficiency improvements across Snapchat's ML Infrastructure
• Develop high-performance embedding generation / batch inference systems to improve model performance
• Develop high-performance data storage/compute systems to improve the efficiency of our ML infrastructure
• Integrate state of the art ML data quality system to assure model performance
• 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

• Strong programming skills in Python, Java, Scala, or C++
• 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
• 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
• 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, * Bachelor's degree in a technical field such as computer science or equivalent experience
• 9+ years of post-Bachelor's software development experience; or Master's degree in a technical field + 5+ years 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

Preferred Qualifications:

• Masters/PhD in a technical field such as computer science or equivalent industry experience
• Experience with big data processing frameworks such as Spark, Flink, or Ray
• Experience with large scale feature store or embedding system
• Familiarity with ML frameworks such as Pytorch, Tensorflow

In the United States, work locations are assigned a pay zone which determines the salary range for the position. The successful candidate's starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. The starting pay may be negotiable within the salary range for the position.These pay zones may be modified in the future.

Zone A (CA, WA, NYC): The base salary range for this position is $229,000-$343,000 annually.

Zone B: The base salary range for this position is $218,000-$326,000 annually.

Zone C: The base salary range for this position is $195,000-$292,000 annually.

This position is eligible for equity in the form of RSUs.

Snap Inc is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together. The Company operates Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world, and Specs Inc., a wholly-owned subsidiary dedicated to making computing more human, in addition to Bitmoji, Saturn, and other digital services. Snap Engineering teams build fun and technically sophisticated products that reach hundreds of millions of Snapchatters around the world, every day. We're deeply committed to the well-being of everyone in our global community, which is why our values are at the root of everything we do. We move fast, with precision, and always execute with privacy at the forefront. You'll play a critical role in scaling our ML Infrastructure, optimizing our embedding, feature and training data storage and compute to enable different paradigms of ML models at massive scale, make Snapchat's ranking and recommendation systems more efficient and impactful., "Default Together" Policy at Snap: At Snap Inc. we believe that being together in person helps us build our culture faster, reinforce our values, and serve our community, customers and partners better through dynamic collaboration. To reflect this, we practice a "default together" approach and expect our team members to work in an office 4+ days per week. At Snap, we believe that having a team of diverse backgrounds and voices working together will enable us to create innovative products that improve the way people live and communicate. Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. EOE, including disability/vets. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, where applicable). Our Benefits: Snap Inc. is its own community, so we've got your back! We do our best to make sure you and your loved ones have everything you need to be happy and healthy, on your own terms. Our benefits are built around your needs and include paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages that let you share in Snap's long-term success!