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Staff Machine Learning Training Framework Engineer, GenAI

at Adobe

Back to all Data Science / AI / ML jobs
A
Industry not specified

Staff Machine Learning Training Framework Engineer, GenAI

at Adobe

Tech LeadNo visa sponsorshipData Science/AI/ML

Posted 4 hours ago

No clicks

Compensation
$172,500 – $306,625 USD

Currency: $ (USD)

City
Not specified
Country
United States

Join Adobe Applied Science & Machine Learning (ASML) as a Staff Machine Learning Training Framework Engineer to design and scale the core training infrastructure behind Adobe’s GenAI foundation models. You will be a senior technical owner for key components of the training framework, translating research needs into reliable, high-performance systems. Your work will enable multiple multimodal and video foundation models by strengthening shared training pipelines across large GPU clusters. You will partner with researchers and infrastructure teams to ensure scalable, reproducible, and performant training workflows.

JOB DESCRIPTION

The Opportunity

Adobe Applied Science & Machine Learning (ASML) is seeking a Staff Machine Learning Training Framework Engineer to play a critical role in building and scaling the core training systems behind Adobe’s generative AI foundation models.

In this role, you will serve as a senior technical owner for key components of our training framework, translating research needs into reliable, scalable, and high‑performance training infrastructure. Rather than focusing on a single model, your work will enable multiple multimodal and video foundation models by strengthening the shared systems used to train them.

You will operate at the intersection of applied research and large‑scale systems execution, ensuring that training workflows are robust, reproducible, and performant across large GPU clusters. This role is ideal for a senior engineer who thrives on deep technical ownership, complex execution, and close collaboration with research teams.

Job Responsibilities

  • Training Framework Ownership: Own the design and implementation of major components of the training framework, including abstractions for model configuration, optimizer and scheduler integration, checkpointing, and experiment management.
  • Large‑Scale Training Execution: Implement and support distributed training strategies such as PyTorch FSDP, Tensor Parallelism, and Pipeline Parallelism, ensuring correctness, stability, and scalability across multi‑node GPU environments.
  • Reliability & Fault Tolerance: Improve the resilience of long‑running training jobs by strengthening restartability, state management, and failure handling mechanisms.
  • Performance‑Aware Framework Design: Identify framework‑level inefficiencies and reduce overhead related to memory usage, communication, or execution orchestration in large training runs.
  • Research Enablement: Partner directly with applied researchers to support new model architectures and training requirements, ensuring the framework adapts quickly to evolving research needs.
  • Training Pipeline Integration: Collaborate with infrastructure and platform teams to integrate the training framework with scheduling, storage, monitoring, and logging systems used in production‑scale environments.

What You’ll Need to Succeed

  • Education: Master’s or PhD degree in Computer Science, Electrical Engineering, or a related field, or equivalent practical experience.
  • Strong Systems Engineering Skills: Proficiency in Python and C++, with experience contributing to large, shared codebases that support multiple users or teams.
  • Proven ML Training Experience: Hands‑on experience training models using PyTorch (or JAX), including multi‑GPU and multi‑node distributed training setups.
  • Distributed Systems Understanding: Solid understanding of synchronization, state management, fault tolerance, and performance tradeoffs in distributed systems.
  • Senior‑Level Execution: Demonstrated ability to independently own complex technical problems, drive solutions to completion, and deliver high‑quality systems relied upon by others.

Preferred Experience

  • Experience supporting large‑scale foundation model training or long‑running multi‑node training jobs.
  • Familiarity with ML training infrastructure such as DeepSpeed, Accelerate, or internal training platforms.
  • Experience working closely with applied research teams on rapidly evolving model requirements.
  • Exposure to profiling, debugging, and optimizing training performance at scale.

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 $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.

Staff Machine Learning Training Framework Engineer, GenAI

at Adobe

Back to all Data Science / AI / ML jobs
A
Industry not specified

Staff Machine Learning Training Framework Engineer, GenAI

at Adobe

Tech LeadNo visa sponsorshipData Science/AI/ML

Posted 4 hours ago

No clicks

Compensation
$172,500 – $306,625 USD

Currency: $ (USD)

City
Not specified
Country
United States

Join Adobe Applied Science & Machine Learning (ASML) as a Staff Machine Learning Training Framework Engineer to design and scale the core training infrastructure behind Adobe’s GenAI foundation models. You will be a senior technical owner for key components of the training framework, translating research needs into reliable, high-performance systems. Your work will enable multiple multimodal and video foundation models by strengthening shared training pipelines across large GPU clusters. You will partner with researchers and infrastructure teams to ensure scalable, reproducible, and performant training workflows.

JOB DESCRIPTION

The Opportunity

Adobe Applied Science & Machine Learning (ASML) is seeking a Staff Machine Learning Training Framework Engineer to play a critical role in building and scaling the core training systems behind Adobe’s generative AI foundation models.

In this role, you will serve as a senior technical owner for key components of our training framework, translating research needs into reliable, scalable, and high‑performance training infrastructure. Rather than focusing on a single model, your work will enable multiple multimodal and video foundation models by strengthening the shared systems used to train them.

You will operate at the intersection of applied research and large‑scale systems execution, ensuring that training workflows are robust, reproducible, and performant across large GPU clusters. This role is ideal for a senior engineer who thrives on deep technical ownership, complex execution, and close collaboration with research teams.

Job Responsibilities

  • Training Framework Ownership: Own the design and implementation of major components of the training framework, including abstractions for model configuration, optimizer and scheduler integration, checkpointing, and experiment management.
  • Large‑Scale Training Execution: Implement and support distributed training strategies such as PyTorch FSDP, Tensor Parallelism, and Pipeline Parallelism, ensuring correctness, stability, and scalability across multi‑node GPU environments.
  • Reliability & Fault Tolerance: Improve the resilience of long‑running training jobs by strengthening restartability, state management, and failure handling mechanisms.
  • Performance‑Aware Framework Design: Identify framework‑level inefficiencies and reduce overhead related to memory usage, communication, or execution orchestration in large training runs.
  • Research Enablement: Partner directly with applied researchers to support new model architectures and training requirements, ensuring the framework adapts quickly to evolving research needs.
  • Training Pipeline Integration: Collaborate with infrastructure and platform teams to integrate the training framework with scheduling, storage, monitoring, and logging systems used in production‑scale environments.

What You’ll Need to Succeed

  • Education: Master’s or PhD degree in Computer Science, Electrical Engineering, or a related field, or equivalent practical experience.
  • Strong Systems Engineering Skills: Proficiency in Python and C++, with experience contributing to large, shared codebases that support multiple users or teams.
  • Proven ML Training Experience: Hands‑on experience training models using PyTorch (or JAX), including multi‑GPU and multi‑node distributed training setups.
  • Distributed Systems Understanding: Solid understanding of synchronization, state management, fault tolerance, and performance tradeoffs in distributed systems.
  • Senior‑Level Execution: Demonstrated ability to independently own complex technical problems, drive solutions to completion, and deliver high‑quality systems relied upon by others.

Preferred Experience

  • Experience supporting large‑scale foundation model training or long‑running multi‑node training jobs.
  • Familiarity with ML training infrastructure such as DeepSpeed, Accelerate, or internal training platforms.
  • Experience working closely with applied research teams on rapidly evolving model requirements.
  • Exposure to profiling, debugging, and optimizing training performance at scale.

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 $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.

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