Launch Potato
Overview
Senior ML Engineer, Recommendation Systems at Launch Potato. You’ll design, deploy, and scale ML systems that power real-time recommendations across millions of user journeys and deliver 100M+ predictions daily. Why Join Us
Launch Potato is a profitable digital media company reaching over 30M+ monthly visitors through brands such as FinanceBuzz, All About Cookies, and OnlyInYourState. As The Discovery and Conversion Company, we connect consumers with leading brands through data-driven content and technology. We’re headquartered in South Florida with a remote-first team spanning over 15 countries, built on speed, ownership, and measurable impact. We convert audience attention into action through data, machine learning, and continuous optimization. You’ll accelerate your career by owning outcomes, moving fast, and driving impact with a global team of high-performers. 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 Compensation
COMPENSATION:
$165,000 - $215,000 per year, paid semi-monthly About Launch Potato
We’re hiring a Machine Learning Engineer (Recommendation Systems) to build the personalization engine behind our portfolio of brands. This role gives you the chance to work on systems serving 100M+ predictions daily, directly impacting engagement, retention, and revenue at scale. Equal Opportunity
Launch Potato is 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, status as a protected veteran, status as an individual with a disability, or other legally protected characteristics.
#J-18808-Ljbffr
Senior ML Engineer, Recommendation Systems at Launch Potato. You’ll design, deploy, and scale ML systems that power real-time recommendations across millions of user journeys and deliver 100M+ predictions daily. Why Join Us
Launch Potato is a profitable digital media company reaching over 30M+ monthly visitors through brands such as FinanceBuzz, All About Cookies, and OnlyInYourState. As The Discovery and Conversion Company, we connect consumers with leading brands through data-driven content and technology. We’re headquartered in South Florida with a remote-first team spanning over 15 countries, built on speed, ownership, and measurable impact. We convert audience attention into action through data, machine learning, and continuous optimization. You’ll accelerate your career by owning outcomes, moving fast, and driving impact with a global team of high-performers. 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 Compensation
COMPENSATION:
$165,000 - $215,000 per year, paid semi-monthly About Launch Potato
We’re hiring a Machine Learning Engineer (Recommendation Systems) to build the personalization engine behind our portfolio of brands. This role gives you the chance to work on systems serving 100M+ predictions daily, directly impacting engagement, retention, and revenue at scale. Equal Opportunity
Launch Potato is 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, status as a protected veteran, status as an individual with a disability, or other legally protected characteristics.
#J-18808-Ljbffr