Research Engineer

The Opportunity

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.

What you'll Do

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. You will have the opportunity to:

• Play a key collaborative role in ambitious research projects
• Be valued as a specialist in your domain of expertise
• Build innovative tool that enables 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

What you need to succeed

• 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

Additional 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++

AI Use Guidelines for Interviews

Our interviews are designed to reflect your own skills and thinking. If these tools are used inappropriately or in a way that misrepresents your work, your application may not move forward in the process.

At Adobe, we empower employees to innovate with AI - and we look for candidates eager to do the same. As part of the hiring experience, we provide clear guidance on where AI is encouraged during the process and where it's restricted during live interviews. See how we think about AI in the hiring experience.

Expected Pay Range

Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $120,700 - $238,600 annually. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process. In Washington, the pay range for this position is $146,300 - $211,850

At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).

In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.