Applied Machine Learning Scientist

StackAdapt Inc.; United States; Remote; USD 100,000 - 138,000; Full time

Job summary

StackAdapt is seeking an Applied Machine Learning Scientist to join an engineering organization powering a large-scale programmatic marketing platform. You will research, prototype, and productionize ML algorithms that improve advertiser ROI and campaign performance.

You design scalable models, translate business objectives into actionable research steps, and collaborate with data engineers to deploy production-grade solutions that blend classical methods with modern techniques.

Qualifications

• Master's degree or PhD in Computer Science, Statistics, Operations Research, or related field.
• Strong command of statistics, optimization, and core machine learning fundamentals.
• Proficiency in coding, data structures, and algorithms.
• Demonstrated ability to break down ambiguous tasks into structured, testable work.
• Comfort working in a friendly, collaborative team environment.

Responsibilities

• Design and innovate machine learning algorithms aimed at maximizing ROI and overall advertising effectiveness, including new approaches and refinements to existing state-of-the-art methods.
• Develop production-grade code, occasionally partnering with data engineers, to deploy novel ML algorithms at scale.
• Prototype algorithms and pipelines, validate them against historical data, and iterate based on empirical insights.
• Translate broadly defined or ambiguous objectives into concrete, actionable research and engineering steps.
• Contribute to a collaborative engineering culture that values statistical rigor and shared learning.

Skills

Statistics

Optimization

Core ML fundamentals

Coding proficiency

Data structures & algorithms

Problem decomposition

Education

Master's or PhD in CS/Statistics/OR

Job description

Role overview

Applied Machine Learning Scientist role within an engineering organization that powers a large-scale programmatic marketing platform handling millions of ad requests per second and billions of automated decisions. The position focuses on researching, prototyping, and productionizing ML algorithms that directly improve advertiser return on investment and campaign performance. The work blends classical methods, state-of-the-art research, and hands-on production coding.

Responsibilities

• Design and innovate machine learning algorithms aimed at maximizing ROI and overall advertising effectiveness, including new approaches and refinements to existing state-of-the-art methods.


• Develop production-grade code, occasionally partnering with data engineers, to deploy novel ML algorithms at scale.


• Prototype algorithms and pipelines, validate them against historical data, and iterate based on empirical insights.


• Translate broadly defined or ambiguous objectives into concrete, actionable research and engineering steps.


• Contribute to a collaborative engineering culture that values statistical rigor and shared learning.

Requirements

• Master's degree or PhD in Computer Science, Statistics, Operations Research, or a closely related field; dual degrees are a plus.


• Strong command of statistics, optimization, and core machine learning fundamentals.


• Proficiency in coding, data structures, and algorithms.


• Demonstrated ability to break down ambiguous tasks into structured, testable work.


• Comfort working in a friendly, collaborative team environment.

Nice to have

• Deep familiarity with both classic ML techniques and modern, state-of-the-art modeling approaches.


• Experience operating at the scale of billions of decisions or millions of requests per second.

Benefits and work setup

• Remote-first arrangement; open to candidates located anywhere in the UK, Ireland, and Germany.


• Highly competitive salary with a posted base range of €87,002–€119,627 EUR, plus potential eligibility for additional compensation such as annual bonuses, commissions, equity awards, and a comprehensive benefits package.


• Retirement or pension savings plan, paid time off including a birthday off, and health benefits from day one.


• Access to a mental health care program, work-from-home reimbursements, and optional global WeWork membership with hubs in London and Toronto.


• Robust onboarding and training program, plus support for personal development such as conferences, courses, and books.


• Parental leave program and a friendly, inclusive culture with social and team events.


• Benefits and perks may vary depending on country of employment and local regulations.