Description
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.
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.
Key responsibilities:
- Play a key collaborative role in ambitious research projects
- Be valued as a specialist in your domain of expertise
- Build innovative tools that enable users to explore their creative potential
- Contribute to existing Adobe tools as well as completely new applications
- Impact products that are used by tens of millions of people
- Learn from your peers and grow into new opportunities
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
Desirable qualifications:
- 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++
The expected pay range for this position is $120,700 - $238,600 annually.