Snap Research serves as an innovation engine for the company. Our projects range from solutions to hard technical problems that significantly enhance Snap’s existing products, to riskier explorations that can lead to fundamental paradigm shifts in the way people communicate and express themselves. The team consists of scientists and engineers who experiment with and invent new technology that has a lasting impact on Snap’s products.
We are looking for a Research Scientist to join the Creative Vision Research Team! At Creative Vision, we focus on making everyone into a creator. We believe creativity is achieved when technology understands the world, humans and objects, provides a range of creative generation and manipulation tools and efficient real-time experiences. Our technology impacts and contributes to multiple products at Snap.
What you’ll do:
- Lead and execute a multi-year research agenda
- Work on large-scale multimodal generative projects
- Share your expertise with other teammates and interns
- Publish your work to top conferences
- Partner with engineering teams to deliver your technology to millions of Snapchatters
Knowledge, Skills, & Abilities:
- Strong technical knowledge of statistics, machine learning, vision and state-of-the-art deep learning literature
- Demonstrated ability in defining, leading and executing challenging research projects
- Strong computer science fundamentals, problem solving skills, programming (Python, C, C++)
- Proven ability to lead interns, PhD students, and junior researchers
Minimum Qualifications:
- PhD in a related technical field such as computer science, statistics, mathematics, machine learning or equivalent years of experience
- Strong theoretical foundations of generative AI and practical experience training, tuning, and modifying generative models
- Track record of publications in top-tier international research venues (e.g. ICLR, AAAI, NeurIPS, CVPR, ECCV, ICCV, SIGGRAPH)
Preferred Qualifications:
- Proven ability to impact product with cutting edge research technology
- Experience with multimodal machine learning, involving images, videos, audio, text, speech
- Knowledge of 3D computer vision, non-rigid and articulated 3D registration and synthesis
- Experience with large-scale data collection and annotation best practices
