Research Scientist, Data-Centric Generative AI

Research Scientist, Data-Centric Generative AI page is loaded## Research Scientist, Data-Centric Generative AI locations:
Los Angeles, California time type:
Full time posted on:
Posted Todayjob requisition :
R0043727is 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 , a visual messaging app that enhances your relationships with friends, family, and the world;

, an augmented reality platform that powers AR across Snapchat and other services; and its AR glasses, .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 t you’ll do:
* Own the data strategy for large-scale multimodal generative models, shaping a multi-year roadmap of model improvements through data acquisition, curation, and usage.
* Design, implement, and operate high-throughput data pipelines for collecting, labeling, and curating multimodal datasets.
* Establish experimentation and evaluation protocols for continuous assessment of data impact on model performance.
* Collaborate with researchers, ML engineers, and infra teams to ensure that data infrastructure integrates cleanly into training, experimentation, and production systems.

Knowledge, Skills, & Abilities:
* Demonstrated ability to define, lead, and execute challenging research or data-centric projects involving large-scale datasets.
* Strong technical knowledge of statistics, machine learning, vision and state-of-the-art deep learning literature
* Strong computer science fundamentals, problem solving, and programming skills (Python required, C/C++ a plus)

Minimum Qualifications:

* PhD in a related technical field such as computer science, statistics, mathematics, machine learning or equivalent years of practical work experience
* Strong theoretical foundations of generative AI and practical experience training, tuning, evaluating and modifying generative models
* Track record of publications in top-tier international research venues (e.g. ICLR, AAAI, NeurIPS, CVPR, ECCV, ICCV, SIGGRAPH)
* Proven ability to lead interns, PhD students, and junior researchers

Preferred Qualifications:

* Proven ability to design, collect, annotate, and evaluate large-scale multimodal datasets
* Familiarity with distributed inference and training across multiple machines and cloud environments
* Experience working with data processing frameworks and distributed systems (Spark, Ray Data, Flink, Beam, or similar).
* Knowledge of tools and frameworks for efficient model inference: model compilation, quantization (e.g. Torch

AO), custom kernels (Triton/CUDA), efficient LLM inference (e.g. vLLM), non-PyTorch runtimes (e.g. ONNX/Tensor

RT).
* Knowledge of photography and video-making techniques, equipment and software

If you have a disability or special need that requires accommodation, please don’t be shy and provide us some ."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…