Senior Machine Learning Engineer, Developer Product Analytics

What you'll do

• Own the full scientific product lifecycle from problem framing and data exploration to model training and production deployment.
• Develop 0-to-1 features that provide actionable insights for content partners, businesses, and global users.
• Translate complex research into practical features in areas like Bayesian methods, privacy-preserving ML, and applied AI.
• Build and maintain high-quality production code using Python to support reusable service designs.
• Drive technical direction by building conviction with senior product and engineering stakeholders.
• Design and deploy machine learning solutions involving supervised/unsupervised learning, time-series modeling, and Bayesian statistics.
• Implement privacy-preserving analytics and statistical experimentation engines for large-scale data platforms.

What we're looking for

• MS or PhD in Statistics, Computer Science, Machine Learning, or a related quantitative field (or equivalent industry experience).
• Proficiency in multiple ML domains including supervised/unsupervised learning, deep learning, time-series modeling, and Bayesian statistics.
• Production-quality software engineering skills in Python, including reusable service design and the full deployment lifecycle.
• Experience taking 0-to-1 features end-to-end from problem framing through production deployment.
• 3-5+ years of industry experience designing and deploying ML or statistical solutions in production.
• Experience with differential privacy, causal inference, or statistical experimentation like A/B testing and Bayesian methods.
• Familiarity with distributed data platforms, web-scale pipelines, and production engineering in Scala or Spark.
• Exposure to applied AI, LLMs, and agentic systems.