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 Adobe Document Cloud Data Science team is on the lookout for an ambitious Machine Learning Engineer to join our dynamic workforce in Waltham, MA. This outstanding opportunity allows you to apply innovative AI/ML techniques and help us build solutions that will drive the success of our Document Cloud business. By collaborating with various business units, you will develop sophisticated data science models addressing challenging issues such as acquisition, engagement, conversion, and retention.

You will have the chance to exercise creativity in problem-solving, delivering inventive new solutions within our data ecosystem. Join a team of skilled engineers dedicated to elevating our customer experiences to the next level!

• Push the boundaries of online recommendation and optimization systems.
• Develop and implement scalable and efficient models on large-scale datasets to address various business problems using sophisticated statistical modeling and machine learning techniques.
• Address complex data science challenges such as online learning and reinforcement learning when tackling business problems in digital marketing.
• Gather, synthesize, and interpret disparate quantitative information sources, develop meaningful insights, and communicate these clearly to key partners.
• Collaborate with product management and engineering groups to develop new products and features.
• Compose a winning culture built on collaboration and shared accomplishments – have fun along the way!

• PhD + 2 years of experience or MS degree in Computer Science, Statistics, Applied Math, Electrical Engineering, Operations Research, Econometrics, or other related fields with 5+ years of experience.
• Solid expertise in machine learning, deep learning, and reinforcement learning.
• Expertise in applying causal inference and experimentation techniques (e.g., uplift modeling, treatment effect estimation, counterfactual analysis) to measure the true incremental impact of personalization and optimization initiatives.
• Ability to develop and enhance personalization using causal signals and machine learning methods (e.g., contextual bandits, reinforcement learning) to drive engagement, conversion, and retention.
• Proficiency in one or more programming languages such as Python.
• Deep understanding of model serving, orchestration, scaling, and GPU resource management.
• Excellent communication and relationship skills, and a great teammate.

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 $125,600 – $234,150 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 $161,700 – $234,150.

In Massachusetts, the pay range for this position is $134,000 – $194,000.

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.