Launch Potato
Senior Machine Learning Engineer, Recommendation Systems
Launch Potato, Las Vegas, Nevada, us, 89105
Overview
Senior Machine Learning Engineer, Recommendation Systems at Launch Potato. You will design, deploy, and scale ML systems that power real-time recommendations across millions of user journeys. This role leads modeling, feature engineering, data pipelines, and experimentation to drive personalization and business impact. Launch Potato is a profitable digital media company with brands such as FinanceBuzz, All About Cookies, and OnlyInYourState. Headquartered in South Florida with a remote-first team spanning over 15 countries, the company operates with speed, ownership, and measurable impact to connect consumers with leading brands through data-driven content and technology. 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, 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) 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. Optimize for latency, throughput, and cost in production. Collaborate with product, engineering, and analytics to launch high-impact personalization features. Implement monitoring systems and maintain clear ownership for model reliability. Qualifications
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). 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 KPIs via ML-powered personalization. Experience with A/B testing platforms and experiment logging best practices. Competencies
Technical Mastery of ML architecture, deployment, and tradeoffs. Experimentation Infrastructure (MLflow, Weights & Biases). Impact-Driven with models that move revenue, retention, or engagement. Collaborative with engineers, PMs, and analysts. Analytical thinking and rigorous test methodologies. Ownership mentality for post-deployment model improvements. Execution-oriented, delivering production-grade systems quickly. Curious and innovative in applying ML advances to personalization. Total Compensation
Base salary is $130,000$220,000 per year, paid semi-monthly. Compensation includes base salary, profit-sharing bonus, and competitive benefits. Future increases are based on company and personal performance. Equal Employment 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, protected veteran status, disability, or other legally protected characteristics. Want to accelerate your career? Apply now! #J-18808-Ljbffr
Senior Machine Learning Engineer, Recommendation Systems at Launch Potato. You will design, deploy, and scale ML systems that power real-time recommendations across millions of user journeys. This role leads modeling, feature engineering, data pipelines, and experimentation to drive personalization and business impact. Launch Potato is a profitable digital media company with brands such as FinanceBuzz, All About Cookies, and OnlyInYourState. Headquartered in South Florida with a remote-first team spanning over 15 countries, the company operates with speed, ownership, and measurable impact to connect consumers with leading brands through data-driven content and technology. 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, 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) 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. Optimize for latency, throughput, and cost in production. Collaborate with product, engineering, and analytics to launch high-impact personalization features. Implement monitoring systems and maintain clear ownership for model reliability. Qualifications
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). 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 KPIs via ML-powered personalization. Experience with A/B testing platforms and experiment logging best practices. Competencies
Technical Mastery of ML architecture, deployment, and tradeoffs. Experimentation Infrastructure (MLflow, Weights & Biases). Impact-Driven with models that move revenue, retention, or engagement. Collaborative with engineers, PMs, and analysts. Analytical thinking and rigorous test methodologies. Ownership mentality for post-deployment model improvements. Execution-oriented, delivering production-grade systems quickly. Curious and innovative in applying ML advances to personalization. Total Compensation
Base salary is $130,000$220,000 per year, paid semi-monthly. Compensation includes base salary, profit-sharing bonus, and competitive benefits. Future increases are based on company and personal performance. Equal Employment 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, protected veteran status, disability, or other legally protected characteristics. Want to accelerate your career? Apply now! #J-18808-Ljbffr