Compute Efficiency Engineer (AI)

TL;DR

Compute Efficiency Engineer (AI): Optimizing AI infrastructure for performance, cost-effectiveness, and sustainability. Focus on telemetry, cost attribution frameworks, and resolving performance bottlenecks across distributed systems.

Location: Must be in one of hirify.global's offices at least 25% of the time (San Francisco, CA | New York City, NY)

Salary: $1 - $2 USD

Company

hirify.global’s mission is to create reliable, interpretable, and steerable AI systems.

What you will do

• Build and evolve telemetry and monitoring systems to provide deep visibility into infrastructure performance, utilization, and costs across our cloud and datacenter fleets.
• Design and implement cost attribution frameworks for our multi-tenant infrastructure, enabling teams to understand and optimize their resource consumption.
• Identify and resolve performance bottlenecks and capacity hotspots through deep analysis of distributed systems at scale.
• Partner closely with cloud service providers and internal stakeholders to optimize cluster configurations, workload placement, and resource utilization across AI training and inference workloads.
• Drive architectural improvements and code-level optimizations across multiple services and platforms to deliver measurable utilization and performance gains.

Requirements

• 6+ years of relevant industry experience, 1+ year leading large scale, complex projects or teams.
• Deep expertise in distributed systems at scale, with a strong focus on infrastructure reliability, scalability, and continuous improvement.
• Strong proficiency in at least one programming language (e.g., Python, Rust, Go, Java).
• Hands-on experience with cloud infrastructure, including Kubernetes, Infrastructure as Code, and major cloud providers such as AWS or GCP.
• Experience optimizing end-to-end performance of distributed systems, including workload right-sizing and resource utilization tuning.
• Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.

Nice to have

• Experience with machine learning infrastructure workloads as well as associated networking technologies like NCCL.
• Low level systems experience, for example linux kernel tuning and eBPF.
• Quickly understanding systems design tradeoffs, keeping track of rapidly evolving software systems.
• Published work in performance optimization and scaling distributed systems.

Culture & Benefits

• Competitive compensation and benefits.
• Optional equity donation matching.
• Generous vacation and parental leave.
• Flexible working hours.
• Lovely office space in which to collaborate with colleagues.

Hiring process

• If we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.