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 and ship 0-to-1 machine learning features used by global content partners and users.
• Translate complex research into production features that deliver materially useful insights.
• Build conviction with senior stakeholders to drive technical direction forward.
• Design and deploy production-quality software using Python, Scala, or Spark.
• Implement privacy-preserving analytics, Bayesian methods, or causal inference solutions.
• Identify high-impact opportunities by working with product managers and cross-functional engineering teams.

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 supervised and unsupervised learning, deep learning, time-series modeling, and Bayesian statistics.
• Production-quality software engineering 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.
• First-principles understanding of ML methods, including explaining algorithm assumptions and failure points.
• 3-5+ years of industry experience designing and deploying ML or statistical solutions in production (preferred).
• Experience with differential privacy, causal inference, or statistical experimentation (preferred).
• Production engineering experience in Scala or Spark (preferred).