Senior ML Engineer Recommendation Systems
@ Launch Potato

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

Your Application Journey

Personalized Resume
Apply
Email Hiring Manager
Interview

Email Hiring Manager

XXXXXXXXX XXXXXXXXXXXXX XXXXXXXX****** @launchpotato.com
Recommended after applying

Job Details

About Launch Potato

Launch Potato is a profitable digital media company reaching over 30M+ monthly visitors with brands like FinanceBuzz, All About Cookies, and OnlyInYourState. With a remote-first team across 15 countries and headquarters in South Florida, the company drives success through speed, ownership, and measurable impact.

Why Join Us?

In this role as the Senior ML Engineer Recommendation Systems, you will accelerate your career by building, deploying, and scaling machine learning systems that power real-time personalized recommendations across millions of user journeys.

Your Role & Responsibilities

  • Build and deploy ML models serving 100M+ predictions daily.
  • Enhance data processing pipelines using Spark, Beam, or Dask.
  • Design ranking algorithms balancing relevance, diversity, and revenue.
  • Deliver real-time personalization with latency less than 50ms.
  • Run statistically rigorous A/B tests to measure business impact.
  • Partner with product, engineering, and analytics teams.
  • Maintain and monitor production systems for reliability and efficiency.

Must Have Qualifications

  • 5+ years experience building and scaling production ML systems.
  • Experience deploying ML systems serving 100M+ predictions daily.
  • Strong background in ranking algorithms including collaborative filtering and deep learning.
  • Proficiency in Python and ML frameworks (TensorFlow or PyTorch).
  • Skilled in SQL and modern data warehouses (Snowflake, BigQuery, Redshift) plus data lakes.
  • Familiarity with distributed computing (Spark, Ray) and LLM/AI agent frameworks.
  • Proven track record of improving business KPIs via ML-powered personalization.
  • Experience with A/B testing platforms and experiment logging best practices.

Competencies

Technical Mastery, Experimentation Infrastructure, Impact-Driven, Collaborative, Analytical Thinking, Ownership Mentality, Execution-Oriented, Curious & Innovative.

Total Compensation

The base salary is set according to market rates and Launch Potato’s Levels Framework. This includes a base salary, profit-sharing bonus, and competitive benefits, with future increases based on company and personal performance.

Key skills/competency

ML, Recommendation, Personalization, Python, TensorFlow, PyTorch, SQL, Spark, A/B Testing, Data Pipelines

Apply without a personalized resume

How to Get Hired at Launch Potato

🎯 Tips for Getting Hired

  • Research Launch Potato's culture: Understand remote-first dynamics, global team structure, and key projects.
  • Tailor your resume: Highlight large-scale ML deployment and personalization expertise.
  • Prepare technical portfolio: Showcase examples of ranking algorithms and real-time ML systems.
  • Practice coding interviews: Focus on Python, ML frameworks, and SQL challenges.
  • Engage on LinkedIn: Network with current employees for insights.

📝 Interview Preparation Advice

Technical Preparation

Review Python and ML framework documentation.
Study ranking algorithm implementations and optimizations.
Practice production-level code and data pipeline setups.
Analyze distributed computing patterns using Spark and Ray.

Behavioral Questions

Describe overcoming challenge in ML deployment.
Explain teamwork on cross-functional projects.
Discuss handling tight deadlines and ownership.
Share a success story improving system reliability.

Frequently Asked Questions