Launch Potato
Overview
Lead ML Engineer, Recommendation Systems
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Launch Potato We are hiring a Machine Learning Engineer (Recommendation Systems) to build the personalization engine behind our portfolio of brands. You’ll design, deploy, and scale ML systems that power real-time recommendations across millions of user journeys, serving 100M+ predictions daily and impacting engagement, retention, and revenue at scale. Headquartered in South Florida with a remote-first team spanning over 15 countries, Launch Potato connects consumers with leading brands through data-driven content and technology. We are a performance-driven company committed to diversity, equity, and inclusion. We are an Equal Employment Opportunity employer and 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, protected veteran status, disability, or other legally protected characteristics. Responsibilities
Drive business growth by building and optimizing the recommendation systems that personalize experiences for millions of users daily. Own modeling, feature engineering, data pipelines, and experimentation to improve personalization. Build and deploy ML models serving 100M+ predictions per day to personalize user experiences at scale. Enhance data processing pipelines (Spark, Beam, Dask) for efficiency and reliability. Design ranking algorithms that balance relevance, diversity, and revenue. Deliver real-time personalization with latency
Run statistically rigorous A/B tests to measure true business impact. Collaborate with product, engineering, and analytics to launch high-impact personalization features. Implement monitoring systems and maintain clear ownership for model reliability. Qualifications and Experience
7+ 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). SQL proficiency and experience with modern data warehouses (Snowflake, BigQuery, Redshift) and data lakes. Familiarity with distributed computing (Spark, Ray) and LLM/AI Agent frameworks. Track record of improving KPIs via ML-powered personalization. Experience with A/B testing platforms and experiment logging best practices. Role and Outcomes
Own the modeling, feature engineering, data pipelines, and experimentation that enable scalable real-time personalization. Deliver ML models and pipelines with robust performance and monitoring. Continually optimize for latency, throughput, and cost in production. Partner with product, engineering, and analytics to ship high-impact personalization features. Maintain model reliability and governance post-deployment. Compensation
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 Potato’s Levels Framework. Your compensation package includes a base salary, profit-sharing bonus, and competitive benefits. Launch Potato is a performance-driven company with future increases based on company and personal performance. Additional Information
Want to accelerate your career? Apply now! We are committed to a diverse, inclusive team and culture. Referrals increase your chances of interviewing at Launch Potato. Get notified about new Machine Learning Engineer jobs in
Cleveland, OH .
#J-18808-Ljbffr
Lead ML Engineer, Recommendation Systems
at
Launch Potato We are hiring a Machine Learning Engineer (Recommendation Systems) to build the personalization engine behind our portfolio of brands. You’ll design, deploy, and scale ML systems that power real-time recommendations across millions of user journeys, serving 100M+ predictions daily and impacting engagement, retention, and revenue at scale. Headquartered in South Florida with a remote-first team spanning over 15 countries, Launch Potato connects consumers with leading brands through data-driven content and technology. We are a performance-driven company committed to diversity, equity, and inclusion. We are an Equal Employment Opportunity employer and 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, protected veteran status, disability, or other legally protected characteristics. Responsibilities
Drive business growth by building and optimizing the recommendation systems that personalize experiences for millions of users daily. Own modeling, feature engineering, data pipelines, and experimentation to improve personalization. Build and deploy ML models serving 100M+ predictions per day to personalize user experiences at scale. Enhance data processing pipelines (Spark, Beam, Dask) for efficiency and reliability. Design ranking algorithms that balance relevance, diversity, and revenue. Deliver real-time personalization with latency
Run statistically rigorous A/B tests to measure true business impact. Collaborate with product, engineering, and analytics to launch high-impact personalization features. Implement monitoring systems and maintain clear ownership for model reliability. Qualifications and Experience
7+ 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). SQL proficiency and experience with modern data warehouses (Snowflake, BigQuery, Redshift) and data lakes. Familiarity with distributed computing (Spark, Ray) and LLM/AI Agent frameworks. Track record of improving KPIs via ML-powered personalization. Experience with A/B testing platforms and experiment logging best practices. Role and Outcomes
Own the modeling, feature engineering, data pipelines, and experimentation that enable scalable real-time personalization. Deliver ML models and pipelines with robust performance and monitoring. Continually optimize for latency, throughput, and cost in production. Partner with product, engineering, and analytics to ship high-impact personalization features. Maintain model reliability and governance post-deployment. Compensation
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 Potato’s Levels Framework. Your compensation package includes a base salary, profit-sharing bonus, and competitive benefits. Launch Potato is a performance-driven company with future increases based on company and personal performance. Additional Information
Want to accelerate your career? Apply now! We are committed to a diverse, inclusive team and culture. Referrals increase your chances of interviewing at Launch Potato. Get notified about new Machine Learning Engineer jobs in
Cleveland, OH .
#J-18808-Ljbffr