Lead Applied 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

Adobe is looking for a Lead Applied Machine Learning Engineer who has an expertise in software engineering and machine learning. This is a tech lead role that combines both coordination skills across ML projects and hands-on delivery.

You will partner with the business units to build and scale data products that address challenging business problems for Adobe’s enterprise customers in a direct co-innovation way. You will research, develop, and deploy large-scale machine learning solutions for business.

What you will Do

Work closely with data scientists, engineers, researchers, and product managers to build AI / ML solutions and Experimentation on Adobe Experience Manager.

Engage with customers to understand and anticipate how machine learning can solve their business problems.

Work across organizational boundaries to align priorities and drive projects forward.

Promote accomplishments across the organization, blogs, and conferences.

What you need to succeed

degree or equivalent experience in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, or related fields.

Proficient in one or more programming languages such as Python, Java, or Scala.

In-depth knowledge of machine learning algorithms and their applications to business problems.

Proven ability in building, deploying, measuring, and maintaining machine learning models.

Proven ability in building large-scale distributed ML pipelines.

Experience with scikit-learn, pandas, ml-lib.

Preferred Qualifications

Proven ability of delivering business solutions or production software.

Experience with Spring Boot, RESTful Web services, Apache Spark, Cosmos DB or similar, MySQL DB or similar.

Experience with hypothesis testing, Bayesian statistics, statistical inference, or multi-armed bandit.

Familiarity with a Deep Learning framework such as TensorFlow or PyTorch.