Launch Potato
Senior ML Engineer, Recommendation Systems
Launch Potato, Chapel Hill, North Carolina, United States, 27517
Overview
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. 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, serving 100M+ predictions daily and directly impacting engagement, retention, and revenue at scale. Base salary:
$130,000$220,000 per year, paid semi-monthly. Responsibilities
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
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
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 Competencies
Technical Mastery: ML architecture, deployment, and tradeoffs Experimentation Infrastructure: MLflow, Weights & Biases Impact-Driven: models that move revenue, retention, or engagement Collaborative: works with engineers, PMs, and analysts Analytical Thinking: analyzes data trends and designs rigorous tests Ownership Mentality: post-deployment ownership and continuous improvement Execution-Oriented: delivers production-grade systems quickly with rigor Curious & Innovative: stays updated on ML advances for personalization Compensation and Benefits
Total compensation includes base salary, profit-sharing bonus, and competitive benefits. Compensation is set according to market rates and varies based on Launch Potatos Levels Framework. We are a performance-driven company with future increases based on company and personal performance. Equal Opportunity
Launch Potato is an Equal Employment Opportunity employer. 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 legally protected characteristics. Application and Location
Were seeking candidates who can contribute to a diverse, inclusive team. If youre inspired by moving fast and delivering impact at scale, apply now. #J-18808-Ljbffr
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. 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, serving 100M+ predictions daily and directly impacting engagement, retention, and revenue at scale. Base salary:
$130,000$220,000 per year, paid semi-monthly. Responsibilities
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
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
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 Competencies
Technical Mastery: ML architecture, deployment, and tradeoffs Experimentation Infrastructure: MLflow, Weights & Biases Impact-Driven: models that move revenue, retention, or engagement Collaborative: works with engineers, PMs, and analysts Analytical Thinking: analyzes data trends and designs rigorous tests Ownership Mentality: post-deployment ownership and continuous improvement Execution-Oriented: delivers production-grade systems quickly with rigor Curious & Innovative: stays updated on ML advances for personalization Compensation and Benefits
Total compensation includes base salary, profit-sharing bonus, and competitive benefits. Compensation is set according to market rates and varies based on Launch Potatos Levels Framework. We are a performance-driven company with future increases based on company and personal performance. Equal Opportunity
Launch Potato is an Equal Employment Opportunity employer. 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 legally protected characteristics. Application and Location
Were seeking candidates who can contribute to a diverse, inclusive team. If youre inspired by moving fast and delivering impact at scale, apply now. #J-18808-Ljbffr