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 degree in a relevant field such as Computer Science or equivalent experience
• 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 let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
• This role might need to be in the office for in-person collaboration 1-2 times a month, therefore you can be located anywhere in the country.

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