Senior ML Engineer Recommendation Systems @ Launch Potato
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About Launch Potato
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, 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 have built a high-growth, high-performance culture where speed, ownership, and measurable impact drive success.
Why Join Us?
At Launch Potato, you will accelerate your career by owning outcomes, moving fast, and driving impact with a global team of high-performers. We convert audience attention into action via data, machine learning, and continuous optimization.
Your Role as Senior ML Engineer Recommendation Systems
You will build the personalization engine behind our portfolio of brands by designing, deploying, and scaling ML systems that power real-time recommendations across millions of user journeys. Your work will directly impact engagement, retention, and revenue at scale, serving over 100M predictions daily.
Must Have Skills
- 5+ years experience building and scaling production ML systems
- Experience deploying ML systems with 100M+ predictions daily
- Strong expertise in ranking algorithms such as collaborative filtering, learning-to-rank, and deep learning
- Proficiency in Python and ML frameworks like TensorFlow or PyTorch
- Skilled with SQL, modern data warehouses (Snowflake, BigQuery, Redshift) and data lakes
- Familiarity with distributed computing frameworks (Spark, Ray) and LLM/AI Agent frameworks
- Experience with A/B testing platforms and experiment logging best practices
Your Mission & Outcomes
Drive business growth by owning the full ML lifecycle: modeling, feature engineering, data pipelines, and experimentation. Specific outcomes include:
- Building and deploying ML models for 100M+ daily predictions
- Enhancing data pipelines using Spark, Beam, or Dask
- Designing ranking algorithms balancing relevance, diversity, and revenue
- Achieving real-time personalization with latency under 50ms
- Conducting rigorous A/B tests to measure business impact
- Optimizing production for latency, throughput, and cost efficiency
- Collaborating with product, engineering, and analytics teams
- Implementing monitoring systems to ensure model reliability
Competencies
This role demands technical mastery of ML systems, a robust experimentation infrastructure (MLflow, W&B), a demonstrable impact-driven approach, strong collaboration, analytical thinking, ownership mentality, a swift execution focus, and constant curiosity about ML advances.
Total Compensation
The base salary is set according to market rates and varies based on Launch Potato’s Levels Framework. The compensation package includes a base salary, profit-sharing bonus, and competitive benefits. Future increases are performance driven.
Equal Employment Opportunity
Launch Potato is committed to diversity, equity, and inclusion. We do not discriminate on any legally protected characteristics.
Key skills/competency
- Machine Learning
- Recommendation Systems
- Personalization
- Ranking Algorithms
- Python
- TensorFlow
- SQL
- Distributed Computing
- A/B Testing
- Data Pipelines
How to Get Hired at Launch Potato
🎯 Tips for Getting Hired
- Customize your resume: Highlight large-scale production ML experiences.
- Showcase projects: Include real-time data and personalization cases.
- Research Launch Potato: Understand their digital media brands and culture.
- Prepare for technical interviews: Brush up on ranking and ML algorithms.