Job description

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 About Adobe Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences. Adobe’s industry-leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity. Our 30,000 employees worldwide are creating the future and raising the bar as we drive the next decade of growth. We’re on a mission to hire the very best and believe in creating a company culture where all employees are empowered to make an impact. At Adobe, we believe that great ideas can come from anywhere in the organization. The next big idea could be yours. Let’s Adobe together At Adobe, we believe in creating a company culture where all employees are empowered to make an impact. Learn more about Adobe life, including our values and culture , focus on people, purpose and community , Adobe for All , comprehensive benefits programs , the stories we tell , the customers we serve, and how you can help us advance our mission of empowering everyone to create. Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other protected characteristic. Learn more. Adobe aims to make our Careers website and recruiting process accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations adobe.com or call 1 408-536-3015. AI Use Guidelines for Interviews: Our interviews are designed to reflect your own skills and thinking. The use of AI or recording tools during live interviews is not permitted unless explicitly invited by the interviewer or approved in advance as part of a reasonable accommodation. 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. State-Specific Notices: California : Fair Chance Ordinances Adobe will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances. Colorado: Application Window Notice If this role is open to hiring in Colorado (as listed on the job posting), the application window will remain open until at least the date and time stated above in Pacific Time, in compliance with Colorado pay transparency regulations. If this role does not have Colorado listed as a hiring location, no specific application window applies, and the posting may close at any time based on hiring needs. Massachusetts: Massachusetts Legal Notice It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Requirements

Must-haves

What you ll Do
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

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

mlaipythonmachine learning

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

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