Machine Learning Engineer

Role Overview

Join the Artificial Intelligence and Machine Learning team as a Machine Learning Engineer. You will build, maintain, and improve production-grade ML systems that power search, recommendations, personalization, computer vision, predictive modeling, and AI-driven experimentation on a global consumer platform.

Responsibilities

• Build, maintain, and improve production ML systems for search/discovery, recommendations, personalization, computer vision, and predictive modeling.
• Improve search and discovery (ranking, filtering, relevance, exact match, boolean logic) and contribute to LLM-powered enhancements.
• Develop and integrate ML models to improve recommendation quality, search accuracy, behavioral analytics, and personalized experiences.
• Write clean, reliable, maintainable code for ML pipelines, model development, experimentation, and production workflows.
• Train, evaluate, monitor, and continually improve models using large-scale datasets.
• Partner with Data Scientists, Product, Engineering, and other teams to translate needs into scalable ML solutions with measurable impact.
• Participate in technical design discussions for ML systems: architecture, data pipelines, evaluation methods, deployment, monitoring, and scalability.

Requirements

• 3+ years experience building, deploying, or maintaining ML systems in production.
• Experience building ML models/systems at scale in areas such as search, recommender systems, personalization, computer vision, predictive modeling, or user-facing ranking.
• Experience on consumer-facing products where ML drives discovery, engagement, retention, or personalization.
• Experience with global-scale, high-traffic systems and/or large-scale user behavior data.
• Strong Python skills.
• Familiarity with ML libraries/frameworks and tooling such as scikit-learn, PyTorch, TensorFlow, XGBoost, pandas, NumPy.
• Ability to reason about ML system design: data quality, evaluation, performance tradeoffs, scalability, reliability, and monitoring.
• Strong communication and cross-functional collaboration skills.

Education

• Bachelor’s degree in Computer Science, Engineering, Data Science, Mathematics, Statistics, or similar; or equivalent practical experience.