Machine Learning Engineer II

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.

At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.

Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.

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.

• →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
• →Thoughtfully leverage AI tools to speed up design, coding, debugging, and documentation, while applying your own critical thinking to validate outputs and explain how you used AI in your workflow.
• →Shape our AI-assisted engineering practices by sharing patterns, guardrails, and learnings with the team so we can safely increase our impact without compromising code quality, reliability, or candidate expectations.

• 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
• Experience using AI coding assistants and agentic tools as a force-multiplier, and equally comfortable solving problems from first principles when those tools aren’t available.
• 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

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

• 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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