Manager, Machine Learning Engineering, Content Recommendation

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’s three core products are Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world; Lens Studio, an augmented reality platform that powers AR across Snapchat and other services; and its AR glasses, Spectacles.

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’s three core products are Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world; Lens Studio, an augmented reality platform that powers AR across Snapchat and other services; and its AR glasses, Spectacles.

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.

We're looking for a Machine Learning Engineering Manager to join the Content Recommendation team at Snap!

What you’ll do:

• Lead a team of machine learning engineers and software engineers in developing and optimizing our personalized video recommendation engine

• Define the overall architecture of the recommender system, ensuring scalability, performance, and reliability

• Drive rapid iteration without compromising quality: work closely with infrastructure engineers to build robust machine learning infrastructure to support the recommender system

• Evaluate the technical tradeoffs in key decision-making processes to ensure optimal outcomes: conduct A/B testing and analyze performance metrics to continuously improve the recommender system.

• Perform design and code reviews to raise technical excellence bar

Knowledge, Skills & Abilities:

• Deep understanding of machine learning approaches, algorithms and their application to recommender system

• Experience setting the direction for teams focused on developing online ranking and recommendation models

• Strong management and mentorship skills, fostering a collaborative and innovative team culture

• Excellent verbal and written communication skills, with meticulous attention to detail

• Ability to effectively collaborate with stakeholders at all levels, both internally and externally

• Proficiency in managing and solving ambiguous problems
   

Minimum Qualifications: 

• Bachelor’s in a related technical field such as computer science or equivalent years of experience

• 8+ years of machine learning industry experience

• 1+ years of experience leading machine learning teams that focus on ranking and/or recommendations

Preferred Qualifications:

• Experience with real-time recommendation systems.

• Experience with creator success ranking and coldstart problems.

• Experience working with large-scale machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks

• Experience working with distributed systems

• Experience working with machine learning, ranking infrastructures, and system designs

• Ability to proactively learn new concepts and apply them at work

If you have a disability or special need that requires accommodation, please don’t 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.

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!

Compensation

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.