Senior ML Engineer Recommendation Systems
@ Launch Potato

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

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Job Details

Who Are We?

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 drive success with speed, ownership, and measurable impact.

Why Join Us?

Accelerate your career by owning outcomes and driving impact with a global high-performance team. We convert audience attention into action through data, machine learning, and continuous optimization.

Must Have

We're looking for someone who has shipped large-scale ML systems into production for personalization. Requirements include:

  • 5+ years of experience in production ML systems.
  • Experience deploying systems with 100M+ predictions daily.
  • Expertise in ranking algorithms including collaborative filtering and deep learning.
  • Proficiency in Python, TensorFlow or PyTorch.
  • Skilled with SQL, Snowflake, BigQuery, or Redshift.
  • Familiarity with distributed computing like Spark or Ray and LLM/AI Agent frameworks.
  • Experience with A/B testing and experiment logging best practices.

Your Role

As a Senior ML Engineer Recommendation Systems, your mission is to drive business growth by building and optimizing recommendation systems for personalized user experiences across millions of journeys. You will manage modeling, feature engineering, data pipelines, and experimentation to enhance personalization and impact business KPIs.

  • Build and deploy models serving 100M+ predictions daily.
  • Enhance data pipelines using Spark, Beam, or Dask.
  • Design efficient ranking algorithms balancing relevance and revenue.
  • Deliver real-time personalization with <50ms latency.
  • Run rigorous A/B tests to gauge business impact.
  • Optimize latency, throughput, and cost efficiency in production.
  • Collaborate closely with product, engineering, and analytics teams.
  • Implement monitoring systems and ensure model reliability.

Competencies

Key traits required include technical mastery of ML architectures, rapid experimentation setup, impact-driven model design, collaborative teamwork, analytical thinking, and strong ownership mentality.

Total Compensation

The base salary is set according to market rates based on Launch Potato’s Levels Framework, inclusive of profit-sharing bonuses and competitive benefits. Compensation increases are performance-driven.

How to Get Hired at Launch Potato

🎯 Tips for Getting Hired

  • Research Launch Potato's culture: Understand their mission and remote-first approach.
  • Customize your resume: Highlight production ML and ranking expertise.
  • Showcase relevant projects: Detail large-scale recommendation systems experience.
  • Prepare for technical interviews: Focus on ML frameworks and data pipelines.

📝 Interview Preparation Advice

Technical Preparation

Review Python and TensorFlow/PyTorch basics.
Practice building scalable ML models.
Brush up on ranking algorithm fundamentals.
Study data pipelines and distributed computing.

Behavioral Questions

Describe teamwork in cross-functional settings.
Explain ownership in past ML projects.
Discuss handling rapid change in projects.
Share examples of problem-solving under pressure.

Frequently Asked Questions