Staff Applied ML Engineer

Responsibilities

• Analyze product and customer data using Python, pandas, SQL, PySpark, or similar tools to identify patterns and modeling opportunities
• Build and productionize ML models for classification, recommendations, similarity, ranking, routing, and prediction use cases
• Design AI-powered workflows that transform unstructured inputs such as tickets, emails, forms, messages, and logs into structured data
• Partner with Engineering teams to integrate ML models and AI workflows into production systems through APIs, services, and automation logic
• Define evaluation methods, telemetry, feedback loops, and monitoring practices for AI-powered product features
• Build reusable patterns, templates, and best practices for data ingestion, feature creation, model usage, and responsible AI implementation
• Provide technical guidance to product teams on AI opportunity sizing, ML design, model trade-offs, and production readiness
• Mentor junior data and ML engineers through code reviews, model reviews, pairing, and technical coaching

Languages