Overview
Senior Machine Learning Engineer, Recommendation Systems at Launch Potato – Join to apply for this role and contribute to personalization across multiple brands.
Why Join Us
Launch Potato is a profitable digital media company reaching 30M+ monthly visitors across 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 are headquartered in South Florida with a remote-first team spanning over 15 countries, fostering a high-growth, high-performance culture where speed, ownership, and measurable impact drive success.
At Launch Potato, you’ll accelerate your career by owning outcomes, moving fast, and driving impact with a global team of high-performers. We develop systems that power real-time recommendations across millions of user journeys and deliver significant engagement, retention, and revenue impact at scale.
Responsibilities
- Drive business growth by building and optimizing the recommendation systems that personalize experiences for millions of users daily
- Own modeling, feature engineering, data pipelines, and experimentation to make personalization smarter, faster, and more impactful
- 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 under 50ms across key product surfaces
- 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 impactExperience deploying ML systems serving 100M+ predictions dailyStrong background in ranking algorithms (collaborative filtering, learning-to-rank, deep learning)Proficiency with Python and ML frameworks (TensorFlow or PyTorch)SQL experience and familiarity with data warehouses (Snowflake, BigQuery, Redshift) and data lakesFamiliarity with distributed computing (Spark, Ray) and LLM / AI Agent frameworksTrack record of improving business KPIs via ML-powered personalizationExperience with A / B testing platforms and experiment logging best practicesCompetencies
Technical Mastery in ML architecture, deployment, and tradeoffsExperimentation Infrastructure (MLflow, Weights & Biases)Impact-Driven with revenue, retention, or engagement focusCollaborative with engineers, PMs, and analystsAnalytical thinking and rigorous test methodologiesOwnership mentality for post-deployment model maintenanceExecution-oriented delivering production-grade systems quicklyCurious and innovative, applying ML advances to personalizationAbout Equal Opportunity
We are committed to an inclusive, diverse 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, status as a protected veteran, status as an individual with a disability, or other legally protected characteristics.
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