Lead Machine Learning Engineer - ML Architect

Our Company

Changing the world through digital experiences is what Adobes all about. We give everyonefrom emerging artists to global brandseverything they need to design and deliver exceptional digital experiences! Were passionate about empowering people to create beautiful and powerful images videos and apps and transform how companies interact with customers across every screen.

Were 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

This role is part of Adobes Global Marketing Organization (GMO) specifically within the Growth Marketing and Insights organization (GMI). We are seeking a highly experienced Lead Machine Learning Engineer to drive the development and deployment of our key data science models into a scalable and robust production system. This role will work closely with our data science engineering and software development teams to craft build and optimize a productiongrade infrastructure for machine learning models. Your expertise will be crucial in translating sophisticated models into robust performant and scalable solutions that drive tangible business value and technological innovation. The perfect candidate will combine advanced technical expertise with strong communication and a dedication to pushing the limits of machine learning engineering.

What youll Do

• Partner with marketing and analytics teams to translate business questions into actionable technical approaches
• Partner with data scientists to refine and deploy models
• Balance technical capabilities with business needs ensuring practical highimpact solutions
• Continuously improve modeling techniques and capabilities as the analytical landscape evolves
• Work with engineering teams to integrate models into production environments
• Implement MLOps standard methodologies covering model governance monitoring retraining and versioning
• Collaborate with software development teams on API development and deployment strategies
• Collaborate with product engineering team to translate our mathematical solutions into a simulation engine product

Required Qualifications

• MS/PhD or equivalent experience in Statistics Economics Mathematics Computer Science or a related quantitative field.
• Deep technical expertise in MMM ML algorithms and causal inference methods.
• Ability to balance business impact with technical feasibility ensuring practical and effective solutions.
• Proven experience developing and productionizing businesscritical models in realworld applications.
• Proficiency in Python R and cloud platforms (e.g. Azure) for scalable model training and deployment.
• Experience with ML model deployment and MLOps frameworks (e.g. MLflow).
• Experience working with engineering and software teams to design scalable infrastructure API development and microservices
• Proven ability to build collaborative multifunctional relationships.
• A curious motivated approach with a passion for learning new skills tools and techniques!

Application Window Notice

If this role is open to hiring in Colorado (as listed on the job posting) the application window will remain open until at least 12:01 AM Pacific Time in compliance with Colorado pay transparency regulations. If this role does not have Colorado listed as a hiring location no specific application window applies and the posting may close at any time based on hiring needs.

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 positionis $142700 $257600 annually. Paywithin this range varies by work locationand may also depend on jobrelated knowledge skillsand 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 shortterm incentives are in the form of sales commission plans. Nonsales roles starting salaries are expressed as base salary and shortterm incentives are in the form of the Annual Incentive Plan (AIP).

In addition certain roles may be eligible for longterm incentives in the form of a new hire equity award.

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