Senior Machine Learning Engineer Recommendation...
@ Launch Potato

Hybrid
$175,000
Hybrid
Full Time
Posted 7 hours ago

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XXXXXXXXX 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 across 15 countries, we drive success with speed, ownership, and measurable impact.

Why Join Us?

At Launch Potato, you accelerate your career by owning outcomes, moving fast, and driving impact with a global high-performing team. We convert audience attention into action through data, machine learning, and continuous optimization.

Your Role as Senior Machine Learning Engineer Recommendation Systems

In this role, you will build the personalization engine behind our brands. You will design, deploy, and scale ML systems that power real-time recommendations across millions of user journeys. Your work will directly affect engagement, retention, and revenue at scale.

Key Responsibilities

  • Build and deploy ML models serving 100M+ predictions per day.
  • Enhance data processing pipelines with tools like Spark, Beam, or Dask.
  • Design ranking algorithms balancing relevance, diversity, and revenue.
  • Deliver real-time personalization with latency under 50ms.
  • Run rigorous A/B tests to measure business impact.
  • Partner with product, engineering, and analytics teams to launch features.
  • Implement monitoring to ensure model reliability.

Required Skills and Experience

  • 5+ years of building and scaling production ML systems.
  • Experience with deploying systems serving 100M+ predictions daily.
  • Expertise in ranking algorithms such as collaborative filtering and learning-to-rank.
  • Proficiency with Python and ML frameworks like TensorFlow or PyTorch.
  • Strong command of SQL and modern data warehouses such as Snowflake, BigQuery, or Redshift.
  • Familiarity with distributed computing (Spark, Ray) and emerging LLM/AI Agent frameworks.
  • Proven record of improving KPIs via ML-driven personalization.
  • Experience with A/B testing and experiment logging best practices.

Compensation & Benefits

Base salary is set based on market rates, with additional profit-sharing bonuses and competitive benefits. Future increases depend on performance, not annual cost adjustments.

Key Skills/Competency

  • Machine Learning
  • Recommendation Systems
  • Personalization
  • Python
  • TensorFlow/PyTorch
  • SQL
  • Ranking Algorithms
  • Distributed Computing
  • A/B Testing
  • Data Engineering

How to Get Hired at Launch Potato

🎯 Tips for Getting Hired

  • Customize Your Resume: Highlight production ML system successes.
  • Emphasize Technical Skills: Detail Python, TensorFlow, SQL expertise.
  • Research Launch Potato: Understand their products and data-driven mission.
  • Practice Interview Insights: Prepare examples of scaling systems.

📝 Interview Preparation Advice

Technical Preparation

Review production ML system architectures.
Practice Python and TensorFlow coding challenges.
Study ranking algorithm case studies.
Brush up on distributed computing fundamentals.

Behavioral Questions

Describe a challenging ML deployment.
Explain team collaboration on projects.
Share a problem-solving success story.
Discuss managing fast-paced environments.

Frequently Asked Questions