Staff Engineer Machine Learning and Data Infrastructure

Skills

About the Role

You will lead the architecture and hands-on development of ML and data infrastructure. You will optimize model performance, build model lifecycle services, design offline and online feature pipelines, improve data correctness and cost, and set technical direction while mentoring engineers across partner disciplines.

Requirements

• Experience building and operating large-scale distributed systems, ML infrastructure, or data platforms
• Experience optimizing production model performance
• Deep knowledge of Databricks and Spark or comparable data platforms
• Knowledge of model training and serving integration, validation, deployment, observability, and rollback
• Python and SQL proficiency
• Proficiency in Java, Scala, Go, C++, or another backend or systems language
• Technical leadership and hands-on engineering experience

Responsibilities

• Improve model inference latency, throughput, resource utilization, and cost
• Build infrastructure for model packaging, versioning, deployment, serving, monitoring, and rollback
• Design and optimize offline data pipelines
• Connect offline and online feature pipelines with consistent definitions, freshness, lineage, and reproducible backfills
• Evolve feature services and data integrations for risk models and decision systems
• Set technical direction, mentor engineers, and lead cross-functional delivery

Benefits

• Team-building programs and company events
• Wellness and meal allowances
• Healthcare coverage for employees and dependants
• Performance bonus
• Long-term incentives
• Medical and financial benefits