Senior ML Engineer, Recommendation Systems

Senior ML Engineer, Recommendation Systems Launch Potato

3 days ago Be among the first 25 applicants.

WHO ARE WE?

Launch Potato is a profitable digital media company that reaches over 30M+ monthly visitors through brands such as FinanceBuzz, All About Cookies, and OnlyInYourState. As The Discovery and Conversion Company, our mission is to connect consumers with the worlds leading brands through data-driven content and technology. Headquartered in South Florida with a remote-first team spanning over 15 countries, weve built a high-growth, high-performance culture where speed, ownership, and measurable impact drive success.

WHY JOIN US?

At Launch Potato, youll accelerate your career by owning outcomes, moving fast, and driving impact with a global team of high-performers. We convert audience attention into action through data, machine learning, and continuous optimization. Were hiring a Machine Learning Engineer (Recommendation Systems) to build the personalization engine behind our portfolio of brands. Youll design, deploy, and scale ML systems that power real-time recommendations across millions of user journeys. This role gives you the chance to work on systems serving 100M+ predictions daily, directly impacting engagement, retention, and revenue at scale.

COMPENSATION

$165,000 - $215,000 per year, paid semi-monthly. Base salary is set according to market rates for the nearest major metro and varies based on Launch Potatos Levels Framework. Your compensation package includes a base salary, profit?sharing bonus, and competitive benefits. Launch Potato is a performance?driven company which means once you are hired, future increases will be based on company and personal performance, not annual cost?of?living adjustments.

MUST HAVE

• 5+ years building and scaling production ML systems with measurable business impact
• Experience deploying ML systems serving 100M+ predictions daily
• Strong background in ranking algorithms (collaborative filtering, learning?to?rank, deep learning)
• Proficiency with Python and ML frameworks (TensorFlow or PyTorch)
• Skilled with SQL and modern data warehouses (Snowflake, BigQuery, Redshift) plus data lakes
• Familiarity with distributed computing (Spark, Ray) and LLM / AI Agent frameworks
• Track record of improving business KPIs via ML?powered personalization
• Experience with A / B testing platforms and experiment logging best practices

YOUR ROLE

Your mission : Drive business growth by building and optimizing the recommendation systems that personalize experience for millions of users daily. Youll own the modeling, feature engineering, data pipelines, and experimentation that make personalization smarter, faster, and more impactful.

OUTCOMES

COMPETENCIES

Since day one, weve been 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.

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