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!

Partnering with the business stakeholders, the selected candidate will be working on the development of various ML models and Generative AI applications that address challenging business problems including product recommendation, user targeting, Agents for workflow optimization and insight generation etc.

You will design and implement an end-to-end ML solution to tackle a business problem. As a hands‑on technical leader, you’ll define the architectural direction, uphold high engineering standards, mentor peers, and drive the productization of the ML solution.

Ideal candidates will have a strong academic background as well as technical skills including generative AI, machine learning, data mining, and software development. Familiarity working with large‑scale datasets and big data techniques would be a plus.

• Design, build, and maintain scalable, production‑grade ML solutions that can work with large‑scale data in production systems
• Lead architectural design and guide the development of optimized ML pipelines
• Collaborate with product management and engineering groups to develop new products and features.
• Define technical direction, conduct building reviews, and establish guidelines for reliability, scalability, and maintainability
• Own and improve CI/CD systems and monitoring pipelines for ML services
• Mentor engineers across ML and backend fields, encouraging a culture of technical excellence

• PhD or MS degree in Computer Science, Statistics, Electrical Engineering, Applied Math, Operations Research, Econometrics, or other related fields.
• 8+ years’ experience building ML solutions and ML systems at scale
• 3+ years’ experience architecting cloud services and infrastructure for large scale use, reliability and performance
• Deep understanding of generative AI, machine learning, deep learning, or data mining concepts, and a track record of solving problems with these methods.
• Proficient in one or more programming languages such as Python, Java and C
• Proven track record of leading complex, high‑stakes technical initiatives across teams
• Strong analytical and quantitative problem‑solving ability.
• Excellent communication, relationship skills and a strong team player.

• Experience with big data techniques
• Experience with building generative AI applications
• Experience with large scale ML systems

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 $162,000 — $301,200 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.

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.

Application…