Staff Engineer, Machine Learning & Data Infrastructure

📋 Description

• Improve model inference latency, throughput, resource utilization, and cost. Profile the full
• Build reusable infrastructure for model packaging, versioning, deployment, serving, monitoring, and
• Design and optimize offline data pipelines on Databricks, Apache Spark, and warehouse/lakehouse
• Connect offline and online feature pipelines, ensuring point-in-time correctness, consistent
• Evolve reliable feature services and data integrations supporting risk models and decision systems.
• Set technical direction, mentor engineers, and lead delivery across ML, data engineering, cloud

🎯 Requirements

• A record of building and operating large-scale distributed systems, ML infrastructure, or data
• Hands-on experience optimizing production model performance, supported by measurable improvements
• Deep understanding of Databricks and Spark, or comparable offline data platforms, including
• Experience with the model lifecycle, including training/serving integration, validation
• Strong Python, SQL, and at least one backend or systems language such as Java, Scala, Go, or C++.
• Ability to turn ambiguous requirements into clear architecture and deliver maintainable systems

🎁 Benefits

• Competitive total compensation package
• L&D programs for employees' growth and development
• Various team building programs and company events
• Wellness and meal allowances
• Comprehensive healthcare schemes for employees and dependants
• More that we love to tell you along the process!