Machine Learning Infrastructure Engineer

Job Summary

Architecting and leading the technical vision for ML platform initiatives, the full-time hybrid Machine Learning Infrastructure Engineer will design scalable infrastructure and oversee the evolution of ML platforms, data systems, and serving infrastructure to enable efficient development and deployment of ML models.

Key responsibilities

• Architect end-to-end ML infrastructure for data processing, feature management, and model serving
• Design and implement next-generation ML platforms that support diverse workloads
• Establish best practices for ML observability, monitoring, and operational excellence

Required qualifications

• 10+ years of software engineering experience, with 5+ years focusing on ML infrastructure
• Deep expertise in distributed systems and data processing at scale
• Strong background in ML platform development and MLOps practices
• Experience building production ML infrastructure for critical business applications
• Proven track record of leading complex technical initiatives