Senior Applied Scientist - Machine Learning Systems Engineer- Photoshop

The Opportunity Photoshop ART is seeking a Senior Machine Learning (ML) Systems

& Efficiency Engineer to join our R&D team focused on delivering practical,

production-ready improvements in inference performance, latency, and cost

efficiency across image editing applications. This role sits at the intersection

of model architecture, systems, inference runtimes, and services, with a clear

mandate: deliver high-quality ML systems at substantially lower cost and higher

efficiency. Individuals in this role are expected to have deep expertise in

areas such as Artificial Intelligence (AI), ML systems, and computer vision.

Strong preference will be given to candidates with experience in distributed

inference, multimodal model profiling, and performance optimization. You will

work closely with research, product, and infrastructure teams to influence model

design decisions, improve GPU utilization, and build scalable, cost-aware ML

systems deployed in production. This is a hands-on, high-leverage role where a

single engineer can drive outsized impact, potentially saving millions of

dollars in compute costs. The ideal candidate will have a strong interest in

developing practical innovations that advance Adobe products. Job

Responsibilities

• Inference & Serving Optimization: Design and optimize
• high-throughput, low-latency inference systems. Optimize model architectures to
• improve deployment and runtime efficiency using techniques such as distillation,
• pruning, quantization, and Mixture-of-Experts (MoE). Implement advanced serving
• strategies including batching, caching (KV, semantic, embedding), quantization
• (FP8/INT8), and distributed inference strategies including data, tensor,
• pipeline, expert, and hybrid parallelism, with a focus on balancing computation
• and communication efficiency. Explore training or fine-tuning approaches when
• they directly lead to more efficient inference, simpler deployment, or improved
• runtime performance. Kernel Development & System Acceleration: Write and
• maintain high-performance GPU kernels using Triton or CUDA to accelerate custom
• model layers and critical workloads. Improve GPU utilization through kernel
• fusion, asynchronous pipelines, and optimized scheduling strategies. Performance
• Profiling & System Optimization: Conduct deep performance analysis using tools
• such as PyTorch Profiler and NVIDIA Nsight to identify bottlenecks in compute,
• memory, and communication. Optimize end-to-end system performance across
• inference workloads. Distributed Systems & Infrastructure Collaboration: Partner
• with infrastructure teams to design scalable and reliable distributed serving
• systems across heterogeneous hardware environments (e.g., A100, H100, B200,
• CPU). Contribute to resource scheduling, GPU pooling, and elastic workload
• management. Cost-Aware ML Engineering: Establish and track efficiency metrics
• such as cost per million inferences. Build benchmarking frameworks and
• dashboards to guide tradeoffs among quality, latency, and compute cost, enabling
• data-driven system and product decisions. Technical Leadership & Best Practices:
• Serve as a trusted technical advisor to research and product teams on efficiency
• tradeoffs. Define best practices for scalable and cost-efficient ML development
• and mentor engineers on performance-oriented systems design. What You’ll Need to
• Succeed Education: Master’s or PhD in Computer Science, Electrical Engineering,
• or a related field, with a focus on machine learning systems, distributed
• systems, or high-performance computing. Distributed Inference & Serving
• Expertise: Hands-on experience implementing and scaling large-scale inference or
• serving workloads using distributed frameworks and runtime systems (e.g.,
• Triton, vLLM, SGLang, xDiT, or similar). Experience applying inference
• compilation and optimization tools (e.g., TensorRT, ONNX Runtime, AOTI),
• including techniques such as operator fusion and graph-level optimization, with
• a strong understanding of system-level performance tradeoffs. GPU & Performance
• Engineering Skills: Strong understanding of GPU architecture (e.g., memory
• hierarchy, compute throughput, communication bandwidth) and practical experience
• diagnosing performance bottlenecks across compute, memory, and I/O subsystems.
• Programming & Systems Development: Proficiency in Python and C++, with
• experience building high-performance or distributed systems. Familiarity with
• CUDA or Triton for performance-critical workloads is highly desirable.
• Data-Driven Engineering Mindset: Demonstrated ability to make engineering
• decisions based on rigorous measurement and benchmarking, with a focus on
• improving system efficiency, scalability, and reliability in production
• environments. Preferred Experience ML Frameworks & Tooling: Experience
• contributing to or maintaining performance- or efficiency-focused libraries or
• systems. Hands-on experience with: Open-source serving frameworks (e.g., vLLM,
• SGLang, xDiT, or similar) Inference compilation tools (e.g., TensorRT, Triton,
• AOTI, or equivalent, operation fusion, or graph-level optimization) GPU
• profiling and performance analysis tools (e.g., PyTorch Profiler, NVIDIA Nsight,
• CUDA tooling) Distributed Systems & Communication: Exposure to low-level
• communication libraries such as NCCL and a practical understanding of collective
• operations (e.g., AllReduce, AllGather) in large-scale distributed serving
• environments. Containerization & Cluster Operations: Familiarity with
• containerized workflows (Docker, Kubernetes) and job scheduling in headless
• Linux environments, including experience operating production ML workloads on
• shared GPU clusters. Model Architectures: Working knowledge of model
• architectures such as Transformers, multimodal models, Mixture-of-Experts (MoE),
• or Diffusion Transformers (DiT).

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 [email protected]

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 $164,000 -- $313,300 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 California, the pay range for

this position is $216,400 - $313,300 In Washington, the pay range for this

position is $204,800 - $296,600 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. At Adobe, you will be

immersed in an exceptional work environment that is recognized around the world.

You will also be surrounded by colleagues who are committed to helping each

other grow through our unique Check-In approach where ongoing feedback flows

freely. If you’re looking to make an impact, Adobe's the place for you. Discover

what our employees are saying about their career experiences on the Adobe Life

blog and explore the meaningful benefits we offer. There's more than meets the

eye when it comes to Adobe. Take the quiz and see how well you know us! 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 applicable characteristics protected by law. Learn more. Adobe aims to

make Adobe.com 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 [email protected] or call (408) 536-3015.