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 Principal Machine Learning, ML Training Platform to join Snap Inc!
What you'll do:
- Design, implement, and scale critical machine learning components and services to support Snap's most strategic initiatives
- Build a next-generation training framework that can support large-scale model training, enabling us to push the limits of what's possible with machine learning
- Perform training and model performance optimization with various GPUs to improve model training speed and efficiency
- Develop an AutoML platform to accelerate model generation and automate the machine learning model lifecycle
- Work across teams to understand product requirements, evaluate trade-offs, and deliver the solutions needed to build innovative products or services
- Advocate for and apply best practices when it comes to availability, scalability, operational excellence, and cost management
- Provide technical direction that influences the entire company
Knowledge, Skills & Abilities:
- Strong understanding of machine learning approaches and algorithms
- Excellent programming and software design skills, including debugging, performance analysis, and test design
- Proven track record of operating highly-available systems at scale
- Ability to proactively learn new concepts and technology and apply them at work
- Skilled at solving ambiguous problems
- Strong collaboration and mentorship skills
Minimum Qualifications:
- BS in technical field such as computer science, mathematics, statistics or equivalent years of experience
- 11+ years of industry machine learning experience
- Experience with GPU/TPU training and optimizations
Preferred Qualifications:
- Masters/PhD in a technical field such as computer science
- Experience leading teams and driving technical roadmaps
- Experience working with machine learning, recommendation and ranking systems, or vector similarity search
- Experience with TensorFlow, PyTorch, or related deep learning frameworks
- Experience with Docker, Kubernetes, Ray, NoSQL solutions, Memcache/Redis, Google/AWS services
- Experienced in MLOps and managing production machine learning lifecycle
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 $244,000-$366,000 annually.
Zone B :
The base salary range for this position is $232,000-$348,000 annually.
Zone C :
The base salary range for this position is $208,000-$311,000 annually.
This position is eligible for equity in the form of RSUs.
What We Do
Snap Inc. is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. We contribute to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together.
Why Work With Us
Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together.
Gallery
Snap Inc. Teams
Snap Inc. Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
Our “default together” approach is an 80/20 model where we are asking team members to spend 80% of the time, on average, in the office, with the remaining 20% of the time spent remote.