Lead Machine Learning Engineer, Ad Performance

Lead Machine Learning Engineer, Ad Performance

As The Discovery and Conversion Company, our mission is to connect consumers with the world’s leading brands through data-driven content and technology.

Headquartered in South Florida with a remote-first team spanning over 15 countries, we’ve built a high-growth, high-performance culture where speed, ownership, and measurable impact drive success.

At Launch Potato, you’ll accelerate your career by owning outcomes, moving fast, and driving impact with a global team of high-performers.

We turn audience attention into action through data, machine learning, and relentless optimization.

Are you a Machine Learning Engineer with a passion for bridging technical expertise and business acumen? Do you thrive in building scalable, reliable systems that directly move revenue? If you’re eager to collaborate globally, face challenges head-on, and make substantial impact, we’re looking for you to join our dynamic team.

In this role, you’ll work at the intersection of advertising algorithms, personalization, and optimization… building the ML software and infrastructure that drives ad performance and user engagement at scale.

You bring both the technical depth to design and deploy complex ML systems and the business intuition to know what actually moves KPIs. Specifically:

• 7+ years of software development and ML engineering, including 3+ years focused on advertising systems
• Proven experience optimizing ad performance using both mature models and emerging ML technologies
• Expertise in one or more ML areas: Recommendation Systems, Advertising Algorithms, NLP, or CV
• Proficiency with Python, SQL, and modern ML frameworks (TensorFlow, PyTorch)
• Familiarity with distributed data processing (Spark, Ray) and cloud infrastructure (AWS/GCP)
• Strong analytical problem-solving skills with a proven track record of delivering measurable results
• Excellent communication, teamwork, and project management skills

Your mission: Elevate Launch Potato’s advertising performance by building scalable, production-ready ML systems that optimize revenue while enhancing user experience. You’ll collaborate across teams to design, deploy, and refine algorithms that improve ad targeting, relevance, and efficiency at global scale.

• Develop and scale advertising algorithms that optimize engagement and revenue simultaneously
• Apply cutting-edge ML approaches (e.g., reinforcement learning, deep learning for ranking) to improve ad performance
• Build scalable infrastructure to support real-time ad decisioning across millions of requests per day
• Conduct rigorous experiments (A/B and multivariate tests) to measure model impact on business KPIs
• Continuously improve ETL pipelines and monitoring systems to ensure reliable ad delivery
• Collaborate with global teams across product, data, and engineering to launch high-impact ad features
• Stay ahead of emerging technologies and integrate them into our ML stack when they create competitive advantage

• Impact-Oriented : You align ML systems to business outcomes and measure what matters
• Technical Builder : You write clean, production-ready code and architect scalable systems
• Collaborative : You work seamlessly with global teams and communicate complex ideas clearly
• Resilient & Determined : You don’t shy from challenges and drive projects through to impact
• Curious Innovator : You keep pace with ML/AI trends and creatively apply them to advertising
• Analytical Problem-Solver : You break down complex systems and find data-driven solutions

We are committed to having a diverse, inclusive team and culture. We are proud to be an Equal Employment Opportunity company. We value diversity, equity, and inclusion.

We do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.