Launch Potato
Senior Machine Learning Engineer, Recommendation Systems
Launch Potato, Seattle, Washington, us, 98127
Overview
Senior Machine Learning Engineer, Recommendation Systems Join to apply for the Senior Machine Learning Engineer, Recommendation Systems role at Launch Potato. About Launch Potato
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. We are a diverse, inclusive team committed to equal employment opportunities. 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 status, or other legally protected characteristics. Role and Responsibilities
Your mission: Drive business growth by building and optimizing the recommendation systems that personalize experiences for millions of users daily. Youll own modeling, feature engineering, data pipelines, and experimentation to make personalization smarter, faster, and more impactful. 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
Must have 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 business KPIs via ML-powered personalization Experience with A/B testing platforms and experiment logging best practices Nice-to-have Experience with MLflow, Weights & Biases (W&B), or similar experimentation infrastructure Compensation and Benefits
Base Salary:
$130,000$220,000 per year, paid semi-monthly Base salary is set according to market rates for the nearest major metro and varies based on Launch Potatos Levels Framework. Your compensation package includes a base salary, profit-sharing bonus, and competitive benefits. Launch Potato is a performance-driven companyfuture increases are based on company and personal performance, not annual cost of living adjustments. Job Details
Seniority level: Mid-Senior level Employment type: Full-time Job function: Engineering and Information Technology Industries: Advertising Services Apply and Additional Info
Want to accelerate your career? Apply now. Referrals increase your chances of interviewing at Launch Potato by 2x. Get notified about new Machine Learning Engineer jobs in Seattle, WA. #J-18808-Ljbffr
Senior Machine Learning Engineer, Recommendation Systems Join to apply for the Senior Machine Learning Engineer, Recommendation Systems role at Launch Potato. About Launch Potato
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. We are a diverse, inclusive team committed to equal employment opportunities. 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 status, or other legally protected characteristics. Role and Responsibilities
Your mission: Drive business growth by building and optimizing the recommendation systems that personalize experiences for millions of users daily. Youll own modeling, feature engineering, data pipelines, and experimentation to make personalization smarter, faster, and more impactful. 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
Must have 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 business KPIs via ML-powered personalization Experience with A/B testing platforms and experiment logging best practices Nice-to-have Experience with MLflow, Weights & Biases (W&B), or similar experimentation infrastructure Compensation and Benefits
Base Salary:
$130,000$220,000 per year, paid semi-monthly Base salary is set according to market rates for the nearest major metro and varies based on Launch Potatos Levels Framework. Your compensation package includes a base salary, profit-sharing bonus, and competitive benefits. Launch Potato is a performance-driven companyfuture increases are based on company and personal performance, not annual cost of living adjustments. Job Details
Seniority level: Mid-Senior level Employment type: Full-time Job function: Engineering and Information Technology Industries: Advertising Services Apply and Additional Info
Want to accelerate your career? Apply now. Referrals increase your chances of interviewing at Launch Potato by 2x. Get notified about new Machine Learning Engineer jobs in Seattle, WA. #J-18808-Ljbffr