Senior Machine Learning Engineer Recommendation... @ Launch Potato
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About Launch Potato
Launch Potato is a profitable digital media company reaching over 30M+ monthly visitors through brands like FinanceBuzz, All About Cookies, and OnlyInYourState. As The Discovery and Conversion Company, its mission is to connect consumers with top global brands using data-driven content and technology. Headquartered in South Florida with a remote-first team spanning 15 countries, the company boasts a high-growth, high-performance culture where speed, ownership, and measurable impact drive success.
Why Join Us?
At Launch Potato, you accelerate your career by owning outcomes, moving fast, and driving impact with a global team of high-performers. The focus is on converting audience attention into action through data, machine learning, and continuous optimization.
Your Role as Senior Machine Learning Engineer Recommendation Systems
As a Senior Machine Learning Engineer Recommendation Systems, your mission is to build the personalization engine behind Launch Potato's portfolio. You will design, deploy, and scale ML systems that serve real-time recommendations across millions of user journeys, directly impacting engagement, retention, and revenue.
Key Responsibilities
- Build and deploy ML models serving 100M+ predictions daily.
- Enhance data processing pipelines using tools like Spark and Beam.
- Design ranking algorithms balancing relevance, diversity, and revenue.
- Deliver real-time personalization with latency under 50ms.
- Run statistically rigorous A/B tests to measure business impact.
- Optimize systems for latency, throughput, and cost efficiency.
- Collaborate with product, engineering, and analytics teams.
- Implement monitoring systems ensuring model reliability.
Must Have Qualifications
- 5+ years experience scaling production ML systems with measurable impact.
- Experience deploying ML systems with 100M+ daily predictions.
- Strong background in ranking algorithms, including collaborative filtering and deep learning.
- Proficient in Python and ML frameworks like TensorFlow or PyTorch.
- Skilled with SQL and modern data warehouses (Snowflake, BigQuery, Redshift) and data lakes.
- Familiarity with distributed computing (Spark, Ray) and LLM/AI Agent frameworks.
- Experience with A/B testing platforms and experiment logging best practices.
Core Competencies
- Technical Mastery in ML architecture, deployment, and tradeoffs.
- Experience in rapid experimentation infrastructures (MLflow, W&B).
- Data-driven impact with models that move revenue, retention, or engagement.
- Collaborative approach with cross-functional teams.
- Strong analytical thinking and rigorous test methodology design.
- Ownership mentality with continuous model improvements.
- Execution focus delivering production-grade systems quickly.
- Curiosity and innovative application of the latest ML advances.
Total Compensation
Base salary is set according to market rates and varies based on Launch Potato’s Levels Framework. The package includes a base salary, profit-sharing bonus, and competitive benefits. Future increases are performance-driven.
Equal Opportunity
Launch Potato is committed to diversity, equity, and inclusion. It is an Equal Employment Opportunity company and does not discriminate based on legally protected characteristics.
Key skills/competency
- Machine Learning
- Recommendation Systems
- Python
- TensorFlow
- PyTorch
- Ranking Algorithms
- SQL
- Distributed Computing
- A/B Testing
- Data Pipelines
How to Get Hired at Launch Potato
🎯 Tips for Getting Hired
- Research Launch Potato's culture: Understand its global, remote-first high-performance environment.
- Customize your resume: Highlight large-scale ML system deployment experience.
- Proof your skills: Emphasize ranking algorithms and personalization expertise.
- Prepare for interviews: Practice discussing ML model optimization and A/B testing.