Lead Machine Learning Engineer

at  Adobe

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
Customer Data Platform (CDP) ML helps enterprise customers to enable data science to drive real-time personalized experiences through Customer AI as well as helps you understand the impact of every marketing dollar spent across paid, earned, and owned channels so you can expertly plan and optimize your marketing investments through Adobe Mix Modeler (AMM) . Customer AI, an embedded AI feature in Adobe Real-Time CDP enables marketers to generate individual level scores for a specific outcome such as conversions or churn. Leads AI in Adobe B2B CDP helps businesses with buying group scores . AMM brings measurement and planning together in a single application to understand campaign performance, effectively forecast plans, and optimize marketing channel investments with greater speed and confidence.
We are looking for a Staff Machine Learning Engineer to build and maintain above mentioned AI applications across B2C and B2B use cases. The candidate shall work closely with Adobe Experience Platform and other business units to integrate these ML solutions into different Adobe enterprise products. 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.
This is an in office position in our San Jose, CA office.
What you’ll Do
Develop models that are required for solving business use cases that can handle data at scale.
Be comfortable building models leveraging large data
Design and build applications powered by 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 you need to succeed

Please refer the Job description for details