Launch Potato
Lead Machine Learning Engineer, Recommendation Systems
Launch Potato, California, Missouri, United States, 65018
Overview
Lead Machine Learning Engineer, Recommendation Systems Launch Potato. The role involves designing, deploying, and scaling ML systems that power real-time recommendations across millions of user journeys, with systems delivering 100M+ predictions daily and impacting engagement, retention, and revenue. Base Salary
BASE SALARY: $130,000$250,000 per year, paid semi-monthly Must Have
Youve shipped large-scale ML systems into production that power personalization at scale. Youre fluent in ranking algorithms and know how to turn data into engagement and conversions. 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 experience for millions of users daily. Youll own the modeling, feature engineering, data pipelines, and experimentation that make personalization smarter, faster, and more impactful. Outcomes
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 Competencies
Technical Mastery: You know ML architecture, deployment, and tradeoffs inside out Experimentation Infrastructure: You set up systems for rapid testing and retraining (MLflow, W&B) Impact-Driven: You design models that move revenue, retention, or engagement Collaborative: You thrive working with engineers, PMs, and analysts to scope features Analytical Thinking: You break down data trends and design rigorous test methodologies Ownership Mentality: You own your models post-deployment and continuously improve them Execution-Oriented: You deliver production-grade systems quickly without sacrificing rigor Curious & Innovative: You stay on top of ML advances and apply them to personalization Total Compensation
Total compensation details: base salary plus incentives and competitive benefits. Launch Potato is a performance-driven company; future increases are based on company and personal performance. Equal Opportunity
We are committed to an equal employment opportunity and 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. Job Details
Seniority level: Mid-Senior level Employment type: Full-time Job function: Engineering and Information Technology Industries: Advertising Services
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Lead Machine Learning Engineer, Recommendation Systems Launch Potato. The role involves designing, deploying, and scaling ML systems that power real-time recommendations across millions of user journeys, with systems delivering 100M+ predictions daily and impacting engagement, retention, and revenue. Base Salary
BASE SALARY: $130,000$250,000 per year, paid semi-monthly Must Have
Youve shipped large-scale ML systems into production that power personalization at scale. Youre fluent in ranking algorithms and know how to turn data into engagement and conversions. 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 experience for millions of users daily. Youll own the modeling, feature engineering, data pipelines, and experimentation that make personalization smarter, faster, and more impactful. Outcomes
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 Competencies
Technical Mastery: You know ML architecture, deployment, and tradeoffs inside out Experimentation Infrastructure: You set up systems for rapid testing and retraining (MLflow, W&B) Impact-Driven: You design models that move revenue, retention, or engagement Collaborative: You thrive working with engineers, PMs, and analysts to scope features Analytical Thinking: You break down data trends and design rigorous test methodologies Ownership Mentality: You own your models post-deployment and continuously improve them Execution-Oriented: You deliver production-grade systems quickly without sacrificing rigor Curious & Innovative: You stay on top of ML advances and apply them to personalization Total Compensation
Total compensation details: base salary plus incentives and competitive benefits. Launch Potato is a performance-driven company; future increases are based on company and personal performance. Equal Opportunity
We are committed to an equal employment opportunity and 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. Job Details
Seniority level: Mid-Senior level Employment type: Full-time Job function: Engineering and Information Technology Industries: Advertising Services
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