Manager, Software Engineering, ML Inference

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. Were 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.

Were looking for a Manager Software Engineering ML Inference to join Snap Inc.!

What youll do:

• Lead and mentor a team of ML Infrastructure engineers responsible for building and scaling the systems that power Snaps 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

Knowledge Skills & Abilities:

• 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

Minimum Qualifications:

• Bachelors degree in a technical field such as computer science or equivalent years of experience

• 9 years of post-Bachelors software engineering experience; or a Masters 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

Preferred Qualifications:

• Advanced degree in a related technical field

• Experience working with ML training platforms inference infrastructure or feature serving systems

• Familiarity with ML frameworks such as TensorFlow PyTorch Caffe2 Spark ML or related frameworks

• Experience with Spark Flink Ray or other big data processing technologies

• Experience with key infrastructure technologies including Kubernetes NoSQL Memcache/Redis Kafka Google Cloud or AWS services

• Track record of delivery in rapidly changing highly collaborative multi-stakeholder environments

• Experience with MLOps and managing production machine learning lifecycle

If you have a disability or special need that requires accommodation please dont be shy and provide us some information.

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 weve 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 Snaps long-term success!

Compensation

In the United States work locations are assigned a pay zone which determines the salary range for the position. The successful candidates 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):

Zone B:

Zone C: