Senior Machine Learning Engineer Recommendation...
@ Launch Potato

Hybrid
$190,000
Hybrid
Full Time
Posted 23 days ago

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XXXXXXXX XXXXXXXXX XXXXXXXXXX***** @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 leading brands including FinanceBuzz, All About Cookies, and OnlyInYourState. Headquartered in South Florida with a remote-first team spanning 15 countries, our high-growth culture values speed, ownership, and measurable impact.

Why Join Us?

At Launch Potato, accelerate your career by owning outcomes, moving fast, and driving impact with a global team. Leverage data, machine learning, and continuous optimization to convert audience attention into action.

Your Role as Senior Machine Learning Engineer Recommendation Systems

You will build, deploy, and scale ML systems powering real-time, personalized recommendations across millions of user journeys. Your responsibilities include:

  • Designing and deploying ML models serving 100M+ predictions daily
  • Enhancing data pipelines with tools like Spark, Beam, and Dask
  • Developing ranking algorithms balancing relevance, diversity, and revenue
  • Implementing A/B testing frameworks and maintaining model reliability
  • Collaborating with cross-functional teams to drive business impact

Key Skills/Competency

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

🎯 Tips for Getting Hired

  • Research Launch Potato's culture: Review mission, brands, and employee testimonials online.
  • Optimize your resume: Highlight production ML systems and personalization impact.
  • Customize your application: Tailor skills in Python, TensorFlow, and Spark.
  • Prepare for interviews: Brush up on ranking algorithms and A/B testing methods.

📝 Interview Preparation Advice

Technical Preparation

Review large-scale ML system case studies.
Practice coding in Python and TensorFlow.
Study ranking and recommendation algorithms.
Benchmark data pipeline optimization techniques.

Behavioral Questions

Describe a high-pressure project you led.
Explain your approach to teamwork and collaboration.
Discuss handling unexpected production issues.
Share a moment of learning from feedback.

Frequently Asked Questions