Description

You will design, implement, and maintain distributed systems to build ML platforms at scale. You will diagnose, fix, and automate complex issues across the stack to ensure maximum uptime and performance. You will extend services to improve platform functionality and reliability while monitoring system performance for cost efficiency. You will collaborate with stakeholders to align internal product needs with end-user requirements.

Responsibilities

• Design and maintain distributed systems for ML platform products
• Diagnose and automate fixes for complex stack issues to ensure uptime
• Extend services to improve platform functionality and reliability
• Monitor system performance and optimize for cost and efficiency
• Collaborate with stakeholders to understand and address internal customer needs

Required Skills

• 3+ years of experience in distributed systems with deep computer science fundamentals
• Extensive programming experience in Java, Python, or Go
• Experience with containerization and orchestration technologies (Docker, Kubernetes)
• Proven track record delivering data and machine learning infrastructure in production
• Experience configuring, deploying, and troubleshooting large-scale production environments
• Designing scalable, highly available systems prioritizing ease of use
• Experience with alerting, monitoring, and remediation automation in distributed environments
• Strong verbal and written communication skills
• B.S., M.S., or Ph.D. in Computer Science, Computer Engineering, or equivalent practical experience

Preferred Skills

• Understanding of the ML lifecycle and state-of-the-art ML Infrastructure technologies
• Experience with GPU and other HPC infrastructure
• Deep understanding of Ray and KubeRay

Key Skills

Education

Any Gradute