Senior ML Engineer Recommendation Systems
@ Launch Potato

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

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XXXXXXXXXX XXXXXXXXXXX XXXXXXXXX******* @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 fosters a culture of speed, ownership, and measurable impact.

Why Join Us?

At Launch Potato, you accelerate your career by owning outcomes and driving impact with a global team of high-performers. You will convert audience attention into actionable insights through data, machine learning, and continuous optimization.

Your Role as a Senior ML Engineer Recommendation Systems

You will build the personalization engine powering recommendation systems across a portfolio of brands. Your role involves designing, deploying, and scaling ML models that serve over 100M+ predictions daily. Your work directly impacts engagement, retention, and revenue.

Key Responsibilities

  • Develop, deploy, and scale ML models for real-time recommendations.
  • Enhance data pipelines using Spark, Beam, or Dask.
  • Design ranking algorithms balancing relevance, diversity, and revenue.
  • Deliver personalized experiences with latency under 50ms.
  • Implement and monitor A/B tests to assess business impact.

Must Have Qualifications

  • 5+ years building and scaling production ML systems with measurable business impact.
  • Experience deploying ML systems serving 100M+ predictions daily.
  • Expertise in ranking algorithms including collaborative filtering, learning-to-rank, and deep learning.
  • Strong proficiency in Python and ML frameworks like TensorFlow or PyTorch.
  • Skilled with SQL and modern data warehouses (Snowflake, BigQuery, Redshift) and data lakes.
  • Familiarity with distributed computing frameworks (Spark, Ray) and LLM/AI Agent frameworks.
  • Experience with A/B testing platforms and experiment logging best practices.

Competencies

Technical Mastery, Experimentation, Impact-Driven Approach, Collaboration, Analytical Thinking, Ownership, Execution Orientation, and Curiosity.

Key skills/competency

  • ML systems
  • Recommendation
  • Personalization
  • Ranking algorithms
  • Python
  • TensorFlow
  • PyTorch
  • SQL
  • Spark
  • A/B testing

How to Get Hired at Launch Potato

🎯 Tips for Getting Hired

  • Research Launch Potato's culture: Understand their digital media mission and impact.
  • Tailor your resume: Highlight scalable ML systems experience.
  • Showcase technical expertise: Emphasize ranking algorithms and Python skills.
  • Practice interview questions: Prepare examples of production ML deployments.

📝 Interview Preparation Advice

Technical Preparation

Review large-scale ML deployment case studies.
Practice Python and TensorFlow coding challenges.
Study ranking algorithm implementations in detail.
Build sample projects with Spark and SQL.

Behavioral Questions

Describe a time you owned project outcomes.
Explain handling scaling challenges under pressure.
Share collaboration experiences with cross-functional teams.
Discuss driving data-driven business results.

Frequently Asked Questions