Asks for

The ad says“Deep understanding of machine learning approaches, algorithms and their application to recommender, ads and search system”
The ad says“Deep understanding of machine learning approaches, algorithms and their application to recommender, ads and search system”
The ad says“Experience working with large-scale machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks”
The ad says“Experience working with distributed systems”
The ad says“Experience on utilizing large language models for tasks like keyword extraction, description generation, and semantic relevance judging”
The ad says“Experience on utilizing large language models for tasks like keyword extraction, description generation, and semantic relevance judging”
The ad says“Deep understanding of machine learning approaches, algorithms and their application to recommender, ads and search system”
The ad says“Experience working with large-scale machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks”
The ad says“Experience working with machine learning, ranking infrastructures, and system designs”
The ad says“Deep understanding of machine learning approaches, algorithms and their application to recommender, ads and search system”
The ad says“Experience working with large-scale machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks”
The ad says“Deep understanding of machine learning approaches, algorithms and their application to recommender, ads and search system”
The ad says“Experience on utilizing large language models for tasks like keyword extraction, description generation, and semantic relevance judging”
The ad says“Experience working with large-scale machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks”
The ad says“Experience working with machine learning, ranking infrastructures, and system designs”
The ad says“Experience working with large-scale machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks”

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.

We're looking for a Machine Learning Engineering Manager to join the Web Ads Ranking team at Snap!

What you’ll do:

Lead a team of machine learning engineers and software engineers to build large-scale indexing, retrieval, and ranking systems that deliver the most relevant Snapchat ads and drive revenue
Collaborate with broad product teams in Snap to define the architecture and vision of the system, and grow the team beyond the initial scope
Build the evaluation framework that enables rapid iteration and high-quality decision-making, working closely with Data Science and Product partners to define success metrics and measure outcomes
Build and grow a high-performing team by raising the bar for engineering and ML excellence, developing talent, and helping shape Snap’s broader machine learning strategy

Knowledge, Skills & Abilities:

Deep understanding of machine learning approaches, algorithms and their application to recommender, ads and search system
Experience on utilizing large language models for tasks like keyword extraction, description generation, and semantic relevance judging
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 post-Bachelor’s ML industry experience; or a Master’s degree in a technical field + 7+ year of post-grad ML experience; or a PhD in a related technical field + 4+ years of post-grad ML experience
1 + year(s) of experience leading machine learning teams teams that focus on ranking or recommendations

Preferred Qualifications:

Experience with real-time recommendation or search ranking systems.
Experience with building LLM based information retrieval or tagging system
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
Experience working with large-scale machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks

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.

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!

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.