Description
We're looking for a Machine Learning Engineer II to join our Growth Platform engineering group. As a Machine Learning Engineer II, you will be responsible for developing and implementing ML models to improve user targeting and personalization for growth initiatives. You will design and build scalable ML pipelines for data processing, model training, and deployment. You will collaborate with cross-functional teams to identify potential ML solutions for growth opportunities. You will conduct A/B tests to evaluate the performance of ML models and optimize their impact on key growth metrics. You will analyze large datasets to extract insights and inform decision-making for user acquisition and retention strategies. You will contribute to the development of our ML infrastructure, ensuring it can support rapid experimentation and deployment. You will stay up-to-date with the latest advancements in ML and recommend new techniques to enhance our growth efforts. You will participate in code reviews and collaborate with team members as needed. You will 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. You will 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.
To be successful in this role, you will need to have 3+ years of experience applying ML to real-world problems, preferably in a growth or user acquisition context. You will need to have excellent communication skills and the ability to work effectively in cross-functional teams. You will need to have strong problem-solving skills and the ability to translate business requirements into technical solutions. You will need to have strong programming skills in Python and experience with PyTorch. You will need to have proficiency in data processing and analysis using tools like SQL, Spark, or Hadoop. You will need to have experience with recommendation systems, user modeling, or personalization algorithms. You will need to have familiarity with statistical analysis. You will need to have 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. You will need to have a Bachelor’s/Master’s degree in a relevant field or equivalent experience.