Launch Potato
Lead ML Engineer, Recommendation Systems
Join Launch Potato, a profitable digital media company that reaches over 30 million monthly visitors through brands such as FinanceBuzz, All About Cookies, and OnlyInYourState.
About Us As a 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.
Compensation $165 000 – $215 000 per year, paid semi‑monthly.
Role Overview 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
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.
Benefits and Perks Base salary, profit‑sharing bonus, and competitive benefits. Launch Potato is a performance‑driven company—future increases are based on company and personal performance, not annual cost‑of‑living adjustments.
Equal Employment Opportunity Launch Potato is a committed Equal Employment Opportunity company. We value diversity, equity, and inclusion 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, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.
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About Us As a 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.
Compensation $165 000 – $215 000 per year, paid semi‑monthly.
Role Overview 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
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.
Benefits and Perks Base salary, profit‑sharing bonus, and competitive benefits. Launch Potato is a performance‑driven company—future increases are based on company and personal performance, not annual cost‑of‑living adjustments.
Equal Employment Opportunity Launch Potato is a committed Equal Employment Opportunity company. We value diversity, equity, and inclusion 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, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.
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