Launch Potato
Lead Machine Learning Engineer, Recommendation Systems
Launch Potato, Charlotte, North Carolina, United States, 28245
Overview
Lead Machine Learning Engineer, Recommendation Systems at Launch Potato. You will design, deploy, and scale ML systems powering real-time recommendations across millions of user journeys and across our portfolio of brands. This role focuses on personalization to drive engagement, retention, and revenue. 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
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) 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 Your Role
Your mission: Drive business growth by building and optimizing the recommendation systems that personalize experiences for millions of users daily. You’ll own the modeling, feature engineering, data pipelines, and experimentation that make personalization smarter, faster, and more impactful. Compensation
Compensation: $165,000 - $215,000 per year, paid semi-monthly Requirements
Must have: You’ve shipped large-scale ML systems into production that power personalization at scale. You’re fluent in ranking algorithms and know how to turn data into engagement and conversions. Benefits & Culture
Total compensation details: Base salary is set according to market rates for the nearest major metro and varies based on Launch Potato’s Levels Framework. Your compensation package includes a base salary, profit-sharing bonus, and competitive benefits. Launch Potato is a performance-driven company, with increases based on company and personal performance. We are committed to a diverse, inclusive team and culture. We are proud to be 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. Headquartered in South Florida with a remote-first team spanning over 15 countries. Note: Referrals increase your chances of interviewing. Get notified about new Machine Learning Engineer jobs in Charlotte, NC.
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Lead Machine Learning Engineer, Recommendation Systems at Launch Potato. You will design, deploy, and scale ML systems powering real-time recommendations across millions of user journeys and across our portfolio of brands. This role focuses on personalization to drive engagement, retention, and revenue. 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
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) 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 Your Role
Your mission: Drive business growth by building and optimizing the recommendation systems that personalize experiences for millions of users daily. You’ll own the modeling, feature engineering, data pipelines, and experimentation that make personalization smarter, faster, and more impactful. Compensation
Compensation: $165,000 - $215,000 per year, paid semi-monthly Requirements
Must have: You’ve shipped large-scale ML systems into production that power personalization at scale. You’re fluent in ranking algorithms and know how to turn data into engagement and conversions. Benefits & Culture
Total compensation details: Base salary is set according to market rates for the nearest major metro and varies based on Launch Potato’s Levels Framework. Your compensation package includes a base salary, profit-sharing bonus, and competitive benefits. Launch Potato is a performance-driven company, with increases based on company and personal performance. We are committed to a diverse, inclusive team and culture. We are proud to be 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. Headquartered in South Florida with a remote-first team spanning over 15 countries. Note: Referrals increase your chances of interviewing. Get notified about new Machine Learning Engineer jobs in Charlotte, NC.
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