Senior ML Engineer Recommendation Systems
@ Launch Potato

Hybrid
$175,000
Hybrid
Full Time
Posted 23 days ago

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XXXXXXXXX XXXXXXXXX XXXXXXX****** @launchpotato.com
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Job Details

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. Headquartered in South Florida with a remote-first team spanning 15 countries, we are driven by speed, ownership, and measurable impact.

Why Join Us?

Accelerate your career by owning outcomes, moving fast, and driving impact with a global high-performance team. As a Senior ML Engineer Recommendation Systems at Launch Potato, you will build the personalization engine powering real-time recommendations for millions of users.

Your Role

You will design, deploy, and scale ML models that serve 100M+ predictions daily. Your responsibilities include modeling, feature engineering, data pipeline optimization, and rigorous A/B testing to enhance business KPIs.

Outcomes

  • Build and deploy ML models serving 100M+ predictions per day.
  • Enhance data pipelines with improved efficiency and reliability.
  • Design ranking algorithms balancing relevance, diversity, and revenue.
  • Deliver real-time personalization with latency under 50ms.
  • Run rigorous A/B tests to quantify business impact.
  • Partner with product, engineering, and analytics teams.
  • Implement robust model monitoring and ownership strategies.

Must Have

5+ years of experience building and scaling production ML systems with measurable impact. You must have shipped systems serving over 100M predictions daily, have expertise in ranking algorithms including collaborative filtering, learning-to-rank, and deep learning, and be proficient in Python with frameworks such as TensorFlow or PyTorch. Experience with SQL, modern data warehouses (Snowflake, BigQuery, Redshift), distributed computing (Spark, Ray), and A/B testing is essential.

Competencies

Technical mastery in ML architecture and deployment, operational expertise in experimentation platforms like MLflow and W&B, and a collaborative, impact-driven mindset to influence business metrics consistently.

Total Compensation

Base salary according to market rates, profit-sharing bonus, and competitive benefits. Future increases are performance-based.

Key skills/competency

  • Machine Learning
  • Recommendation Systems
  • Ranking Algorithms
  • Data Pipelines
  • A/B Testing
  • Python
  • TensorFlow
  • PyTorch
  • Distributed Computing
  • Personalization
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How to Get Hired at Launch Potato

🎯 Tips for Getting Hired

  • Customize your resume: Highlight ML system deployment experiences.
  • Showcase technical skills: Emphasize Python and ML frameworks.
  • Research Launch Potato: Understand their digital media impact.
  • Prepare for interviews: Practice real-time personalization scenarios.

📝 Interview Preparation Advice

Technical Preparation

Review large-scale ML system architectures.
Practice ranking algorithm implementations.
Study distributed computing frameworks.
Simulate real-time prediction deployments.

Behavioral Questions

Describe a high-pressure ML project.
Explain collaborative problem-solving with cross-teams.
Share experiences handling rapid deployments.
Discuss ownership in projects.

Frequently Asked Questions