ML Hardware Fleet Operations Manager

Amazon Web Services (AWS); Austin (TX); On-site; USD 175,000 - 237,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Annapurna Labs (U.S.) Inc. in Austin, TX is seeking a Manager for MLA Fleet Operations. You will lead a team of engineers across multiple ML accelerator platforms, drive 6–12 month roadmaps, and own fleet health, automation, and data infrastructure.

You will coordinate with hardware and software teams to deliver reliable, scalable ML infrastructure. You will define the team roadmap, mentor engineers, and communicate progress in executive reviews.

Qualifications

• Bachelor’s degree in computer science, electrical engineering, or related field.
• 7+ years in systems engineering, platform engineering, SRE, or hardware operations.
• 2+ years of engineering team management experience.
• Knowledge of Python scripting and debugging hardware.
• Experience with large-scale distributed systems or web services.

Responsibilities

• Build, hire, mentor, and grow a team of platform development engineers for ML fleet operations.
• Define team roadmap and strategy for fleet health, automation, and data infrastructure.
• Drive operational excellence with metrics, SLAs, and scalable processes.
• Partner with hardware/software/product teams to prioritize debug efforts and fixes.
• Own escalation paths for critical fleet incidents and lead cross-functional war rooms.
• Present fleet insights to senior leadership with data-driven narratives.

Skills

Python scripting

Hardware troubleshooting

Large-scale distributed systems

SRE

Team management

Education

Bachelor's degree in CS/EE

Tools

GPU hardware

Job description

Annapurna Labs (U.S.) Inc. in Austin, TX is seeking a Manager for MLA Fleet Operations. You will lead a team of engineers across multiple ML accelerator platforms, drive 6–12 month roadmaps, and own fleet health, automation, and data infrastructure.

You will coordinate with hardware and software teams to deliver reliable, scalable ML infrastructure. You will define the team roadmap, mentor engineers, and communicate progress in executive reviews.