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Jobs / Machine Learning Engineer in United States of America
18 days ago
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Adobe·SaaS·18 days ago
18 days ago

Senior Machine Learning Engineer, AI Platform

San Jose, United States of AmericaSenior · 5-8 yearsMachine Learning Engineer

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Must-have skills for this role

  • python
  • kubernetes
  • distributed systems
  • cloud infrastructure

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What you'll do

  • Own the architecture and roadmap for major components of the ML compute and inference platform, such as training orchestration, GPU scheduling and utilization, model serving, or the developer-facing surfaces ML teams build on.
  • Design and operate distributed systems that run large-scale training and low-latency, high-throughput inference reliably across thousands of accelerators.
  • Drive multi-tenancy, elasticity, and cost/utilization efficiency across a shared GPU fleet serving many teams with competing demands.
  • Build the paths that move a model from experiment to production without re-implementation, from packaging and registry through deployment and safe rollout.
  • Set engineering standards for reliability, observability, and performance, and raise the bar for how the platform is built and operated.
  • Partner with ML researchers and product teams to turn emerging workloads into first-class platform capabilities, and inform capacity and hardware strategy.
  • Provide technical leadership and mentorship across the platform organization.

What they're looking for

  • 7+ years building and operating large-scale platform, infrastructure, or distributed systems in production, with direct ownership of performance, scalability, and reliability.
  • Deep expertise in distributed systems and cloud infrastructure, including Kubernetes, containerized workloads, and operating large multi-node and multi-region clusters.
  • Strong programming ability in Python and at least one systems language (Go, C++, Rust, or Java).
  • A track record of designing systems that other engineers build on, making deliberate architectural tradeoffs and taking them from design to production at scale.
  • A bias for measurable outcomes (latency, throughput, utilization, reliability) and the collaboration skills to drive them across teams and partners.

Nice to have

  • Experience with GPU or accelerator scheduling, performance tuning, or fleet management.
  • Familiarity with ML framework internals or distributed training (PyTorch, FSDP, DeepSpeed) or modern inference stacks (vLLM, TensorRT-LLM, Triton, Ray Serve).
  • Experience operating ML or data infrastructure at the scale of a major ML-driven product organization

Summarised by NextRaise from the employer’s description, which follows in full below.

Full description from employer

The Opportunity

Adobe's AI and generative AI products, from Firefly to the intelligence built into Creative Cloud and Experience Cloud, run on a shared compute and inference platform. It's the infrastructure every internal ML team uses to train models and serve them to production at global scale.
As a Staff Machine Learning Platform Engineer, you'll own core parts of that platform. That means extracting maximum utilization from large GPU fleets, moving models from experiment to production without a rewrite, and serving inference at low latency and high throughput under real traffic. You set technical direction rather than take tickets, and the architecture you define shapes how hundreds of engineers across Adobe train and ship AI.

Key Responsibilities
● Own the architecture and roadmap for major components of the ML compute and inference platform, such as training orchestration, GPU scheduling and utilization, model serving, or the developer-facing surfaces ML teams build on.
● Design and operate distributed systems that run large-scale training and low-latency, high-throughput inference reliably across thousands of accelerators.
● Drive multi-tenancy, elasticity, and cost/utilization efficiency across a shared GPU fleet serving many teams with competing demands.
● Build the paths that move a model from experiment to production without re-implementation, from packaging and registry through deployment and safe rollout.
● Set engineering standards for reliability, observability, and performance, and raise the bar for how the platform is built and operated.
● Partner with ML researchers and product teams to turn emerging workloads into first-class platform capabilities, and inform capacity and hardware strategy.
● Provide technical leadership and mentorship across the platform organization.


Required Qualifications
● 7+ years building and operating large-scale platform, infrastructure, or distributed systems in production, with direct ownership of performance, scalability, and reliability.
● Deep expertise in distributed systems and cloud infrastructure, including Kubernetes, containerized workloads, and operating large multi-node and multi-region clusters.
● Strong programming ability in Python and at least one systems language (Go, C++, Rust, or Java).
● A track record of designing systems that other engineers build on, making deliberate architectural tradeoffs and taking them from design to production at scale.
● A bias for measurable outcomes (latency, throughput, utilization, reliability) and the collaboration skills to drive them across teams and partners.


Nice to Have
● Experience with GPU or accelerator scheduling, performance tuning, or fleet management.
● Familiarity with ML framework internals or distributed training (PyTorch, FSDP, DeepSpeed) or modern inference stacks (vLLM, TensorRT-LLM, Triton, Ray Serve).
● Experience operating ML or data infrastructure at the scale of a major ML-driven product
organization


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.


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 $172,500 -- $306,625 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 $211,800 - $306,625


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.

SaaS

Company

AdobeSaaS
San Jose, United States of America

Company facts come from this company's own listings. We only show what the postings themselves carry.

Sourced from Adobe's careers site·first seen 3 Sept 2026·last verified 8 Sept 2026·How we source jobs

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