Launch Potato
Senior Machine Learning Engineer, Recommendation Systems
Launch Potato, Charlotte, North Carolina, United States, 28245
Overview
Senior Machine Learning Engineer, Recommendation Systems – Launch Potato. Join to apply for the
Senior Machine Learning Engineer, Recommendation Systems
role at
Launch Potato . We’re hiring a Machine Learning Engineer (Recommendation Systems) to build the personalization engine behind our portfolio of brands. You’ll design, deploy, and scale ML systems that power real-time recommendations across millions of user journeys, serving 100M+ predictions daily and impacting engagement, retention, and revenue at scale. COMPENSATION:
$165,000 - $215,000 per year, paid semi-monthly. WHO WE ARE 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 world’s leading brands through data-driven content and technology. Headquartered in South Florida with a remote-first team spanning over 15 countries, we’ve built a high-growth, high-performance culture where speed, ownership, and measurable impact drive success. WHY JOIN US At Launch Potato, you’ll accelerate your career by owning outcomes, moving fast, and driving impact with a global team of high-performers. We convert audience attention into action through data, machine learning, and continuous optimization. This role gives you the chance to work on systems serving 100M+ predictions daily, directly impacting engagement, retention, and revenue at scale.
YOUR ROLE Your mission: Drive business growth by building and optimizing the recommendation systems that personalize experience for millions of users daily. You’ll own the modeling, feature engineering, data pipelines, and experimentation that make personalization smarter, faster, and more impactful.
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, W&B, rapid testing and retraining
Impact-Driven: Models that move revenue, retention, or engagement
Collaborative: Works well with engineers, PMs, and analysts
Analytical Thinking: Designs rigorous test methodologies
Ownership Mentality: Post-deployment ownership and ongoing improvement
Execution-Oriented: Production-grade systems delivered quickly with rigor
Curious & Innovative: Keeps up with ML advances and applies to personalization
Compensation & Benefits Total Compensation 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 future increases based on company and personal performance.
EEO Statement We are committed to having a diverse, inclusive team and culture. We are proud to be an Equal Employment Opportunity employer. We value diversity, equity, and inclusion. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, gender identity, 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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Senior Machine Learning Engineer, Recommendation Systems – Launch Potato. Join to apply for the
Senior Machine Learning Engineer, Recommendation Systems
role at
Launch Potato . We’re hiring a Machine Learning Engineer (Recommendation Systems) to build the personalization engine behind our portfolio of brands. You’ll design, deploy, and scale ML systems that power real-time recommendations across millions of user journeys, serving 100M+ predictions daily and impacting engagement, retention, and revenue at scale. COMPENSATION:
$165,000 - $215,000 per year, paid semi-monthly. WHO WE ARE 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 world’s leading brands through data-driven content and technology. Headquartered in South Florida with a remote-first team spanning over 15 countries, we’ve built a high-growth, high-performance culture where speed, ownership, and measurable impact drive success. WHY JOIN US At Launch Potato, you’ll accelerate your career by owning outcomes, moving fast, and driving impact with a global team of high-performers. We convert audience attention into action through data, machine learning, and continuous optimization. This role gives you the chance to work on systems serving 100M+ predictions daily, directly impacting engagement, retention, and revenue at scale.
YOUR ROLE Your mission: Drive business growth by building and optimizing the recommendation systems that personalize experience for millions of users daily. You’ll own the modeling, feature engineering, data pipelines, and experimentation that make personalization smarter, faster, and more impactful.
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, W&B, rapid testing and retraining
Impact-Driven: Models that move revenue, retention, or engagement
Collaborative: Works well with engineers, PMs, and analysts
Analytical Thinking: Designs rigorous test methodologies
Ownership Mentality: Post-deployment ownership and ongoing improvement
Execution-Oriented: Production-grade systems delivered quickly with rigor
Curious & Innovative: Keeps up with ML advances and applies to personalization
Compensation & Benefits Total Compensation 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 future increases based on company and personal performance.
EEO Statement We are committed to having a diverse, inclusive team and culture. We are proud to be an Equal Employment Opportunity employer. We value diversity, equity, and inclusion. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, gender identity, 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
Get notified about new Machine Learning Engineer jobs in Charlotte, NC.
#J-18808-Ljbffr