Launch Potato
Senior Machine Learning Engineer, Recommendation Systems
Launch Potato, Henderson, Nevada, us, 89077
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, with systems serving 100M+ predictions daily. 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 (W&B) Impact-Driven: Models that move revenue, retention, or engagement Collaborative: Works with engineers, PMs, and analysts Analytical Thinking: Designs rigorous test methodologies Ownership Mentality: Post-deployment model ownership and improvement Execution-Oriented: Production-grade systems with rigor Curious & Innovative: Applies ML advances to personalization Compensation
BASE SALARY: $130,000$220,000 per year, paid semi-monthly. Total compensation includes base salary, profit-sharing bonus, and benefits. Compensation may vary based on Launch Potatos Levels Framework. Role Context
Your mission is to drive business growth by personalizing experiences for millions of users daily. Youll own modeling, feature engineering, data pipelines, and experimentation to make personalization smarter, faster, and more impactful. About Launch Potato & Equal Opportunity
Launch Potato is a profitable digital media company reaching 30M+ monthly visitors with brands such as FinanceBuzz, All About Cookies, and OnlyInYourState. We are an Equal Employment Opportunity company committed to diversity, equity, and inclusion. We do not discriminate based on race, religion, color, national origin, gender, pregnancy, sexual orientation, gender identity or expression, age, veteran status, disability, or any other legally protected characteristics. We are remote-first, with headquarters in South Florida and a global team across 15+ countries. #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, with systems serving 100M+ predictions daily. 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 (W&B) Impact-Driven: Models that move revenue, retention, or engagement Collaborative: Works with engineers, PMs, and analysts Analytical Thinking: Designs rigorous test methodologies Ownership Mentality: Post-deployment model ownership and improvement Execution-Oriented: Production-grade systems with rigor Curious & Innovative: Applies ML advances to personalization Compensation
BASE SALARY: $130,000$220,000 per year, paid semi-monthly. Total compensation includes base salary, profit-sharing bonus, and benefits. Compensation may vary based on Launch Potatos Levels Framework. Role Context
Your mission is to drive business growth by personalizing experiences for millions of users daily. Youll own modeling, feature engineering, data pipelines, and experimentation to make personalization smarter, faster, and more impactful. About Launch Potato & Equal Opportunity
Launch Potato is a profitable digital media company reaching 30M+ monthly visitors with brands such as FinanceBuzz, All About Cookies, and OnlyInYourState. We are an Equal Employment Opportunity company committed to diversity, equity, and inclusion. We do not discriminate based on race, religion, color, national origin, gender, pregnancy, sexual orientation, gender identity or expression, age, veteran status, disability, or any other legally protected characteristics. We are remote-first, with headquarters in South Florida and a global team across 15+ countries. #J-18808-Ljbffr