Sr. Machine Learning Engineer

Our Company

Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen. 

We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!

 

The Opportunity

Experience Intelligence team is looking for a Senior Full-stack ML Engineer, for Content Generation team, to lead the development of research level PoCs into production systems such as Genstudio for Performance Marketing. You will drive system design, ML model assessment, the development of production data/ML pipelines, automation architecture, visualizations and system deployment. Your work will directly impact our customer's ability to generate high-performing and on-brand marketing content at scale. If you have a passion for shipping groundbreaking data-driven customer-facing features, learning new technologies every day, and working on high visibility projects with ample room for creativity, this might be a good fit for you. You will join a diverse, lively group of engineers and scientists long established in the ML space. The work is dynamic, fast-paced, creative, collaborative and data-driven.

What you'll Do

• Develop models essential for solving business use cases that handle data at scale.
• Architect and optimize end-to-end ML pipelines, ensuring scalability, efficiency, and robustness.
• Understand data to recommend the right models, evaluation metrics, and governance approaches.
• Engage in the full product lifecycle, including architecture, design, deployment, and production operations of ML models and systems.

What you need to succeed

• Master's degree in Computer Science, Computer Engineering, or a related field—or equivalent experience.
• 5+ years of proven experience as a Machine Learning Engineer with a track record of successfully delivering machine learning projects to customers.
• 2+ years of strong hands-on experience working on generative AI technology such as LLM, evals, LLM-as-a-judge, fine-tuning, etc.
• Strong Python and deep learning engineering skills with experience in one or more training or deployment environments (PyTorch, TensorFlow).
• Experience with LLM frameworks and tools such as Hugging Face, LangChain, PEFT, and LlamaIndex.
• Experience with deployment technologies such as Docker and knowledge of ML Ops and ML services is a plus.
• Experience with cloud platforms such as Azure and AWS is a plus.
• Excellent problem-solving skills, with the ability to analyze complex issues and drive solutions with a data-driven approach.
• Strong verbal and written communication skills, with proven ability to work in cross-functional teams.

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 $142,700 -- $257,600 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.

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 posti