Lead Machine Learning Engineer - ML Architect
Adobe Software
JOB LEVEL
P40EMPLOYEE ROLE
Individual ContributorThe Opportunity
This role is part of Adobe’s 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 production-grade 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 you'll Do
- Partner with marketing execution 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, high-impact 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 business-critical models in real-world 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, multi-functional 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 position is $142,700 -- $257,600 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.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.
Adobe will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances.Internal Opportunities
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