About the Company
Snap Inc. is a technology company focused on improving the way people live and communicate through the camera. Their core products include Snapchat, Lens Studio, and Spectacles. The Cameos team within Snap is dedicated to innovating new ways for Snapchatters to express themselves with friends through customizable short, looping videos.
About the Role
As a Machine Learning Engineer on the Cameos Team, you will play a crucial role in leading augmented reality innovations. You will contribute to features that empower users to create amazing AR experiences. This role involves developing and deploying robust machine learning frameworks, exploring state-of-the-art algorithms, and collaborating with various Snap teams to prototype new product features, all while creating products used by millions of Snapchatters.
What you'll do:
- Develop and deploy production-quality machine learning frameworks for on-device and backend inference.
- Explore and implement state-of-the-art algorithms to keep Snap products on the cutting-edge of machine learning and generative AI technology.
- Work closely with other Snap teams to explore and prototype new product features.
- Create products that are used by millions of Snapchatters.
- Drive the technical and organizational roadmap for the engineering team.
- Lead and grow a team of exceptional machine learning engineers.
- Influence key decisions on architecture and implementation of scalable, reliable, and cost-effective engineering solutions.
Knowledge, Skills, Abilities:
- Strong understanding of machine learning approaches and algorithms.
- Ability to proactively learn new concepts and apply them at work.
- Strong communication, presentation, and interpersonal skills.
- Ability to lead and represent the team’s goals and projects with cross-functional business partners and leaders.
Minimum Qualifications:
- Bachelor’s degree in a technical field such as computer science or years of equivalent experience.
- Research or engineering experience in deep learning with one or more of the following: generative models, segmentation, object detection, classification, model optimizations (e.g. pruning, quantization, distillation).
- Experience working with machine learning frameworks such as PyTorch, TensorFlow.
Preferred Qualifications:
- Advanced degree in machine learning, computer vision, or related field.
- Experience developing and optimizing real-time software for mobile applications.
- Experience with generative modeling for computer vision applications.
- Experience with text-to-image generative models.
- Experience with high-throughput ML inference at scale.
- Experience optimizing ML inference on the backend.