Senior Machine Learning Engineer Recommendation...
@ Launch Potato

Hybrid
$220,000
Hybrid
Full Time
Posted 7 hours ago

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Job Details

About Launch Potato

Launch Potato is a profitable digital media company reaching over 30M+ monthly visitors across brands like FinanceBuzz, All About Cookies, and OnlyInYourState. Headquartered in South Florida with a remote-first team spanning over 15 countries, the company is known for its high-growth, high-performance culture where speed, ownership, and measurable impact drive success.

Why Join Us?

At Launch Potato, you accelerate your career by owning outcomes and driving impact with a global team of high-performers. The company leverages data, machine learning, and continuous optimization to convert audience attention into action.

Your Role as Senior Machine Learning Engineer Recommendation Systems

You will build and optimize the personalization engine powering real-time recommendations across millions of user journeys. This role focuses on designing, deploying, and scaling ML systems that serve over 100M+ predictions daily, directly impacting engagement, retention, and revenue.

Key Responsibilities

  • Build and deploy ML models serving 100M+ predictions daily
  • Enhance data processing pipelines using tools like Spark, Beam, and Dask
  • Design robust ranking algorithms balancing relevance, diversity, and revenue
  • Ensure real-time personalization with latency under 50ms
  • Conduct statistically rigorous A/B tests to validate business impact
  • Partner with product, engineering, and analytics teams to launch features
  • Implement monitoring systems and maintain model reliability

Must Have Qualifications

  • 5+ years of experience building and scaling production ML systems
  • Experience deploying ML systems with 100M+ daily predictions
  • Strong knowledge in ranking algorithms such as collaborative filtering and learning-to-rank
  • Proficiency in Python and frameworks like TensorFlow or PyTorch
  • Skilled in SQL and experience with data warehouses and data lakes
  • Experience with distributed computing frameworks like Spark and Ray
  • Familiarity with LLM/AI Agent frameworks and A/B testing methodologies

Competencies

  • Technical Mastery in ML architecture and deployment
  • Effective Experimentation Infrastructure setup (MLflow, W&B)
  • Impact-Driven mindset to improve business KPIs
  • Collaborative work with cross-functional teams
  • Strong analytical skills to interpret data trends
  • Ownership mentality with continuous model improvements
  • Fast execution in delivering production-grade systems
  • Curiosity and innovation in applying ML advances

Total Compensation & Benefits

The base salary is set according to market rates and includes profit-sharing, bonus, and competitive benefits. Compensation adjustments are performance-driven.

Key skills/competency

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

How to Get Hired at Launch Potato

🎯 Tips for Getting Hired

  • Customize your resume: Highlight production ML system experience.
  • Showcase technical projects: Emphasize recommendation algorithms.
  • Research Launch Potato: Understand their digital media brands.
  • Prepare for interviews: Focus on ML deployment challenges.

📝 Interview Preparation Advice

Technical Preparation

Review ML model deployment frameworks.
Practice ranking algorithms with sample datasets.
Learn Spark and distributed computing techniques.
Set up a mini recommendation engine project.

Behavioral Questions

Describe a challenge in scaling ML systems.
Explain collaboration with cross-functional teams.
Discuss handling tight deadlines in production.
Share continuous improvement examples post-deployment.

Frequently Asked Questions