Senior ML Engineer Recommendation Systems
@ Launch Potato

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

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XXXXXXXXXX XXXXXXXXXXX XXXXXXXX******* @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 over 15 countries, the company is known for its high-growth, high-performance culture driven by speed, ownership, and measurable impact.

Why Join Us?

As a Senior ML Engineer Recommendation Systems, you will accelerate your career by owning outcomes, moving fast, and driving impact. You will work on building the personalization engine driving the recommendations across millions of user journeys, directly impacting engagement, retention, and revenue at scale.

Your Role

Your mission is to build and optimize machine learning systems for real-time recommendations. Responsibilities include:

  • Building and deploying ML models serving over 100M+ predictions per day
  • Enhancing data processing pipelines using Spark, Beam, or Dask
  • Designing ranking algorithms balancing relevance, diversity and revenue
  • Delivering real-time personalization with sub-50ms latency
  • Running rigorous A/B tests to measure business impact
  • Optimizing systems for latency, throughput, and cost efficiency
  • Partnering with cross-functional teams to launch key features
  • Implementing monitoring systems and ensuring model reliability

Must Have

5+ years of experience building and scaling production ML systems with measurable business impact. Expertise in ranking algorithms (collaborative filtering, learning-to-rank, deep learning), Python, ML frameworks (TensorFlow or PyTorch), SQL with modern data warehouses, distributed computing (Spark, Ray) and familiarity with LLM/AI Agent frameworks.

Competencies

  • Technical Mastery
  • Experimentation Infrastructure
  • Impact-Driven
  • Collaborative
  • Analytical Thinking
  • Ownership Mentality
  • Execution-Oriented
  • Curious & Innovative

Compensation

Base salary is determined based on market rates for major metros. The compensation package includes a base salary, profit-sharing bonus, and competitive benefits. Future salary increases are based on company and personal performance.

Key Skills/Competency

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

🎯 Tips for Getting Hired

  • Customize your resume: Highlight ML systems and personalization projects.
  • Showcase relevant skills: Emphasize Python, TensorFlow, and SQL expertise.
  • Prepare case studies: Detail experiences with production ML systems.
  • Practice interviews: Focus on technical and analytical scenarios.

📝 Interview Preparation Advice

Technical Preparation

Review ranking algorithm concepts.
Practice ML model deployment techniques.
Optimize data pipeline exercises.
Refine coding in Python and SQL.

Behavioral Questions

Discuss collaboration with cross-functional teams.
Explain decision-making under pressure.
Describe handling project ownership.
Share experience with rapid testing.

Frequently Asked Questions