- Develop monitoring, diagnostics, and alerting systems that surface actionable insights on
efficiency, utilization, reliability, and cost trends.
- Establish incident response processes, runbooks, and documentation that enable
operational excellence.
- Proactively anticipate system failures and implement preventive measures, reducing
operational toil and improving system resilience.
A day in the life
Each day you will work with some of the best engineers in the industry to develop Machine
Learning Accelerators. On-site in Austin, Texas, you will be part of the team that develops
custom silicon and contribute to the infrastructure that enables this innovation.
You might start your day investigating anomalies in job completion rates or resource utilization
patterns. You could spend your morning collaborating with a design verification team to optimize
their regression workflows, identifying bottlenecks and proposing improvements. In the
afternoon, you might be building new tooling that simplifies infrastructure access for emulation
teams, or contributing to monitoring dashboards that give teams real-time visibility into their
development velocity.
You'll participate in design reviews, contribute to postmortems when incidents occur, and
continuously refine the systems that accelerate the path from RTL to silicon. Throughout the
day, you'll balance immediate customer needs—unblocking a team waiting for compute capacity
—with longer-term platform investments. You'll write code, review infrastructure-as-code
changes, and collaborate across teams who depend on the systems you build.
Take a look inside our labs to see what you will learn at Annapurna Labs: