Research Engineer

Adobe•Seattle, WA

47d

About The Position

The Research Engineering & Design Lab within Adobe Research is looking for a Research Engineer with a passion for the unique challenges involved in the development of high-performance ML models, with a particular focus on optimizing the resource consumption of large-scale generative models, including for cloud and on-device deployment. Join our efforts to turn cutting-edge research into new products and features in Adobe's web, desktop and mobile applications, and expand what's possible in tools for creative expression. At Adobe Research, you will work closely with both scientists and engineers to ensure that new technologies being developed for generative AI models, image processing, audio, video, animation, 3D and vector graphics will run efficiently in-cloud and on a variety of platforms. You'll help adapt models and algorithms to the limitations of different systems and devices.

Requirements

Passion for model optimization/compression and high-performance computing
Solid deep learning skills, including practical experience in computer vision/natural language processing
Knowledgeable about the current state of the art in ML efficiency
Experience in improving the efficiency of mid- to large-scale ML models
Software engineering expertise
Proficiency with Python and ML libraries like PyTorch, TensorFlow, JAX, or similar
Strong communication and collaboration skills
Ph.D. /Master's degree in Computer Science or a related field, or 3 years of industry experience

Nice To Haves

Knowledge of state-of-the-art machine learning methods for large scale multimodal models
Experience on diffusion model optimization, neural network pruning/knowledge distillation/quantization/architecture search, sub-quadratic attention optimization, efficient architecture design and on-device ML
Experience with sparse mixture of experts and related techniques
Experience running ML models within a deployment environment (using TensorRT, AITemplate, CoreML, WinML, TensorFlow Lite, ONNXRuntime or similar)
Hands-on experience in designing ML models between different platforms (Cloud, mobile, in-browser, etc.)
Knowledge of design techniques for mobile-friendly ML models
Proficiency with C++