Machine Learning Engineer 2

Adobe • San Jose, CA

1d

About The Position

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 Machine Learning Engineer to understand & optimize the experience of Adobe’s Digital Experience customers. Partnering with Adobe Research and other business units, the candidate will build products that transform the way companies approach audience creation, journey optimization, and personalization at scale. You will join a diverse, collaborative, lively group of engineers and scientists long established in the ML space. The work is dynamic, fast-paced, creative, and data-driven.

Requirements

• MS or PhD degree in Computer Science, Data Science or related field required.
• Deep understanding of statistical modeling, machine learning, or analytics concepts, and a track record of solving problems with these method
• Ability to quickly learn new skills and work in a fast-paced team.
• Proficient in one or more programming languages such as Python, Scala, Java, SQL.
• Proficient in ML frameworks such as scikit-learn, SparkML, TensorFlow or PyTorch.
• Excellent problem-solving and analytical skills.
• Excellent communication and relationship building skills.

Responsibilities

• Develop innovative models in partnership with Adobe Research
• Design and build applications powered by GenAI models and predictive models, including working on traditional engineering problems such as defining APIs, integrating with UIs, deploying on Cloud services, CICD, etc., as well as implementing ML-Ops best practices.
• Understand data to make recommendation for the right predictive models, quality metrics and governance approaches.
• Engage in product lifecycle – architecture, design, deployment, and production operations.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees