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 such as FinanceBuzz, All About Cookies, and OnlyInYourState. Our mission is to connect consumers with the world’s leading brands through data-driven content and technology. Headquartered in South Florida with a remote-first team spanning over 15 countries, we foster a high-growth, high-performance culture driven by 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 of high-performers. We convert audience attention into action through data, machine learning, and continuous optimization. As the Senior ML Engineer Recommendation Systems, you will build the personalization engine behind our portfolio of brands, powering real-time recommendations across millions of user journeys.

Your Role

Your mission: Drive business growth by building and optimizing recommendation systems for millions of users daily. You will own modeling, feature engineering, data pipelines, and experimentation to make personalization smarter, faster, and more impactful.

  • Develop ML models serving 100M+ predictions per day.
  • Enhance data processing pipelines with Spark, Beam, or Dask.
  • Design ranking algorithms balancing relevance, diversity and revenue.
  • Deliver real-time personalization with latency under 50ms.
  • Implement rigorous A/B testing to measure business impact.

Must Have

An extensive background in building and scaling production ML systems along with expertise in ranking algorithms, Python ML frameworks, SQL, distributed computing, and hands-on experience in improving business KPIs through personalization.

Competencies and Outcomes

You are expected to have technical mastery, a collaborative spirit, and a strong ownership mentality. Your responsibilities include driving business growth via ML-powered personalization, optimizing data pipelines, running A/B tests, and ensuring model reliability.

Total Compensation

The base salary is competitive and aligned with market rates, along with profit-sharing bonuses and benefits. Compensation adjustments are performance based.

Key skills/competency

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

How to Get Hired at Launch Potato

🎯 Tips for Getting Hired

  • Research Launch Potato's culture: Study the company values and team dynamics.
  • Customize your resume: Highlight production ML and recommendation projects.
  • Prepare detailed case studies: Bring examples of scaling ML systems.
  • Practice technical interviews: Review Python, ML frameworks, and SQL challenges.

📝 Interview Preparation Advice

Technical Preparation

Review Python and TensorFlow basics.
Practice building large-scale ML pipelines.
Study ranking algorithm implementations.
Revisit distributed computing concepts like Spark.

Behavioral Questions

Describe times you led project ownership.
Discuss collaboration with cross-functional teams.
Explain handling tight deadlines and quick delivery.
Share examples of data-driven decision making.

Frequently Asked Questions