Machine Learning Engineer - Marketing

About the Role

Key Responsibilities

• Build and own scalable ML systems that optimize affiliate partner performance across multiple dimensions (e.g., ROAS, incremental trips, cost efficiency).
• Design and implement data pipelines that integrate internal and partner data sources to support model training and inference.
• Develop and deploy machine learning models that power partner-level recommendations and budget allocation strategies.
• Build APIs and backend services to deliver model outputs to internal tools and external platforms.
• Collaborate with Data Engineering and vendors to productize the affiliate optimization solution, ensuring reliability, observability, and maintainability.
• Support CI/CD workflows using tools like Jenkins and GitHub to ensure rapid iteration and deployment.
• Partner with analytics and marketing stakeholders to translate business goals into ML solutions and measure impact through experimentation.

Requirements

• 2+ years of experience building end-to-end machine learning models and data-intensive systems in production.
• Proficiency in Python, Java, or C/C++, with experience developing and integrating APIs.
• 2+ years of experience with MLOps and DevOps tools such as Jenkins, GitHub, or GitLab, including CI/CD pipeline management.
• Practical experience working in cloud environments such as Azure, AWS, or GCP.
• Familiarity with Snowflake or BigQuery for data warehousing and analytics.
• Experience executing and measuring A/B tests and other experimentation frameworks.
• Experience implementing AI solutions that integrate with business systems to enhance functionality and user interaction.
• Experience working in agile teams with a focus on rapid delivery and iterative development.

Nice to Have

• Experience with Affiliate, Paid Media, or performance marketing product development.
• Experience designing and building distributed, data-intensive products, including frontend and web app development.
• Familiarity with Generative AI and agentic design principles.
• Proficiency in mathematical analysis, machine learning, statistical analysis, and predictive modeling.

Qualifications

• Bachelor's degree or equivalent work experience in Computer Science, Engineering, Mathematics, Statistics, or a related discipline.
• Master's degree preferred.

Benefits & Perks

• Affordable medical plan options, a 401(k) plan (including matching company contributions), and an employee stock purchase plan.
• No-cost programs for all colleagues including wellness screenings, tobacco cessation and weight management programs, confidential counseling and financial coaching.
• Benefit solutions that address the different needs and preferences of our colleagues including paid time off, flexible work schedules, family leave, dependent care resources, colleague assistance programs, tuition assistance, retiree medical access and many other benefits depending on eligibility.