Principal Scientist - Data Pipeline Engineer

Adobe; San Francisco; On-site; VES 188,574,000 - 354,662,000; Full time

Job summary

Adobe seeks a Principal ML Engineer to optimize cost per asset and boost throughput across ML pipelines behind multimodal foundation models. You will own end-to-end economics of turning billions of raw assets into training-ready data, influencing modeling and infrastructure teams.

The role requires 10+ years in ML systems, strong Python and systems languages, and experience scaling data pipelines. You will collaborate with data platforms and modeling teams to deliver cost-efficient, high-quality

Qualifications

• 10+ years in ML systems, ML infrastructure, or applied ML engineering at scale.
• Proven track record cutting the cost of large-scale ML data pipelines.
• Deep expertise in optimizing inference for VLMs/LLMs and distillation.
• Experience with data curation and data quality for training generative or multimodal models.
• Strong Python and at least one systems language (C++, Rust, Go, Java); distributed frameworks such as Ray or Spark.
• Clear communication across modeling, infrastructure, and data teams.
• Bachelor's, Master's, or Ph.D. in CS, Engineering, ML, or a related field.

Responsibilities

• Own cost per asset across the full pipeline, including compute, storage, data access and movement, and reprocessing.
• Optimize pipeline DAGs to cut cost, such as running cheap filters first to reduce waste.
• Improve throughput of pipelines running VLMs, LLMs, captioners, embedding and quality models via batching, parallelism, quantization, and serving optimizations.
• Distill larger models into smaller, cheaper ones while preserving labeling and filtering quality.
• Decide where specialized models, general models, or cascades give the best cost/quality tradeoff.
• Build evaluation frameworks to ensure efficiency gains don't degrade data quality.
• Develop a deep understanding of what makes data valuable for training LLMs, VLMs, and diffusion models, encoding it into filtering, scoring and selection.
• Partner with modeling teams to connect pipeline changes to training outcomes.
• Work with data platform teams on orchestration (e.g., Ray), scheduling, and storage for cost-efficient ML workloads.

Skills

ML systems

ML infra

Python

C++

Rust

Ray

Spark

Communication

Education

Bachelor's/Master's/PhD in CS/Engineering/ML

Tools

Ray

Spark

Job description

About The Role

We're looking for a Principal ML Engineer to drive down cost per asset and drive up throughput across the ML pipelines behind Adobe's multimodal foundation models (image, video, audio). You'll own the end-to-end economics of turning billions of raw assets into training-ready data, making it faster and cheaper without sacrificing data quality. This is a senior individual contributor role with broad influence across modeling and infrastructure teams.

What You'll Do

• Own cost per asset across the full pipeline, including compute (GPU and CPU), storage, data access and movement, and reprocessing, and identify the biggest levers to reduce it
• Optimize pipeline DAGs to cut cost, such as running cheap filters first so expensive model stages only process the assets that matter and reduce waste from unnecessary duplications
• Improve throughput of pipelines running specialized and general-purpose models (VLMs, LLMs, captioners, embedding and quality models) through batching, parallelism, quantization, and serving optimizations
• Distill larger models into smaller, cheaper ones that preserve labeling and filtering quality
• Decide where specialized models, general models, or cascades give the best cost/quality tradeoff
• Build evaluation frameworks to ensure efficiency gains don't degrade training data quality
• Develop a deep understanding of what makes data valuable for training LLMs, VLMs, and diffusion models, and encode it into filtering, scoring, and selection
• Partner with modeling teams to connect pipeline changes to training outcomes
• Work with data platform teams on orchestration (e.g., Ray), scheduling, and storage so ML workloads run cost-efficiently on shared infrastructure

What You Need To Succeed

• 10+ years in ML systems, ML infrastructure, or applied ML engineering, including work at billions-of-assets scale
• Track record of cutting the cost of large-scale ML data pipelines across compute, storage, and data access (e.g., early filtering, deduplication, model cascades)
• Deep expertise in optimizing inference for VLMs, LLMs, or other large models, including batching, quantization, serving, and distillation
• Experience with data curation and data quality for training generative or multimodal models
• Strong Python, plus a systems-level language (C++, Rust, Go, or Java), and experience with distributed frameworks such as Ray or Spark
• Clear communication across modeling, infrastructure, and data teams
• Bachelor's, Master's, or Ph.D. in CS, Engineering, ML, or a related field

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.

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 the website or complete the application process, email [e-mail].

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 positionis $206,300 - $388,000 annually. Paywithin this range varies by work locationand 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 $268,000 - $388,000 In Washington, the pay range for this position is $247,200 - $357,900

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.