Machine Learning Engineer II

We’re looking for a machine learning engineer II in our Growth Platform engineering group. You’ll join a small and focussed team who will help us to understand our users better so we can drive engagement and growth, and to improve their user experience.

What you'll do:

• Develop and implement ML models to improve user targeting and personalization for growth initiatives
• Design and build scalable ML pipelines for data processing, model training, and deployment
• Collaborate with cross-functional teams to identify potential ML solutions for growth opportunities
• Conduct A/B tests to evaluate the performance of ML models and optimize their impact on key growth metrics
• Analyze large datasets to extract insights and inform decision-making for user acquisition and retention strategies
• Contribute to the development of our ML infrastructure, ensuring it can support rapid experimentation and deployment
• Stay up-to-date with the latest advancements in ML and recommend new techniques to enhance our growth efforts
• Participate in code reviews and collaborate with team members as needed

What we're looking for:

• 3+ years of experience applying ML to real-world problems, preferably in a growth or user acquisition context
• Excellent communication skills and ability to work effectively in cross-functional teams 
• Strong problem-solving skills and ability to translate business requirements into technical solutions
• Strong programming skills in Python and experience with PyTorch
• Proficiency in data processing and analysis using tools like SQL, Spark, or Hadoop
• Experience with recommendation systems, user modeling, or personalization algorithms
• Familiarity with statistical analysis
• Bachelor’s/Master’s degree in a relevant field or equivalent experience.
• Nice to have:
  • Experience with Natural Language Processing (NLP) to enhance user targeting and personalization strategies
  • Proficiency in data visualization techniques
  • Experience with cloud platforms (e.g., AWS) and containerization technologies (e.g., Docker, Kubernetes)
  • Contributions to open-source ML projects or research publications

Relocation Statement:

•  This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

In-Office Requirement Statement:

• We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.
• This role will need to be in the office for in-person collaboration 1-2 times per month and therefore needs to be in a commutable distance from one of the following offices: Dublin.

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