Launch Potato
Lead Machine Learning Engineer, Recommendation Systems
Launch Potato, Cincinnati, Ohio, United States, 45208
Overview
Lead Machine Learning Engineer, Recommendation Systems at Launch Potato Launch Potato is a profitable digital media company reaching over 30M+ monthly visitors with brands such as FinanceBuzz, All About Cookies, and OnlyInYourState. We connect consumers with leading brands through data-driven content and technology. Headquartered in South Florida with a remote-first team spanning over 15 countries, we foster a high-growth, high-performance culture where speed, ownership, and measurable impact drive success. 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, with systems serving 100M+ predictions daily and a potential impact on engagement, retention, and revenue at scale. Base salary:
$130,000–$250,000 per year, paid semi-monthly. Responsibilities
Your mission: 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, speed, and impact. Build and deploy ML models serving 100M+ predictions per day to personalize user experiences at scale. Enhance data processing pipelines (Spark, Beam, Dask) with efficiency and reliability improvements. Design ranking algorithms that balance relevance, diversity, and revenue. Deliver real-time personalization with latency under 50ms across key product surfaces. Run statistically rigorous A/B tests to measure true business impact. Optimize for latency, throughput, and cost efficiency in production. Partner with product, engineering, and analytics to launch high-impact personalization features. Implement monitoring systems and maintain clear ownership for model reliability. Qualifications
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 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. Compensation & Benefits
Your compensation package includes a base salary, profit-sharing bonus, and competitive benefits. We operate as a performance-driven company, with future increases based on company and personal performance. Employment details
Location: Remote-friendly; Headquarters in South Florida. Employment type: Full-time. Seniority level: Mid-Senior level. Equal Opportunity
Launch Potato is 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, veteran status, disability, or other legally protected characteristics.
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Lead Machine Learning Engineer, Recommendation Systems at Launch Potato Launch Potato is a profitable digital media company reaching over 30M+ monthly visitors with brands such as FinanceBuzz, All About Cookies, and OnlyInYourState. We connect consumers with leading brands through data-driven content and technology. Headquartered in South Florida with a remote-first team spanning over 15 countries, we foster a high-growth, high-performance culture where speed, ownership, and measurable impact drive success. 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, with systems serving 100M+ predictions daily and a potential impact on engagement, retention, and revenue at scale. Base salary:
$130,000–$250,000 per year, paid semi-monthly. Responsibilities
Your mission: 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, speed, and impact. Build and deploy ML models serving 100M+ predictions per day to personalize user experiences at scale. Enhance data processing pipelines (Spark, Beam, Dask) with efficiency and reliability improvements. Design ranking algorithms that balance relevance, diversity, and revenue. Deliver real-time personalization with latency under 50ms across key product surfaces. Run statistically rigorous A/B tests to measure true business impact. Optimize for latency, throughput, and cost efficiency in production. Partner with product, engineering, and analytics to launch high-impact personalization features. Implement monitoring systems and maintain clear ownership for model reliability. Qualifications
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 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. Compensation & Benefits
Your compensation package includes a base salary, profit-sharing bonus, and competitive benefits. We operate as a performance-driven company, with future increases based on company and personal performance. Employment details
Location: Remote-friendly; Headquarters in South Florida. Employment type: Full-time. Seniority level: Mid-Senior level. Equal Opportunity
Launch Potato is 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, veteran status, disability, or other legally protected characteristics.
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