Member of Technical Staff (AI)

Location: San Mateo or New York, United States

Salary: $200,000–$230,000 per year

Company

hirify.global provides a platform for building, training, and serving specialized AI models across text, image, embedding, audio, and multimodal workloads.

What you will do

• Design, build, and operate core infrastructure for large-scale AI training and inference.
• Develop benchmarks, traces, and simulators to evaluate scheduling, caching, and network performance.
• Identify and eliminate bottlenecks across kernels, drivers, scheduler policies, storage, and networking.
• Turn research ideas into production systems that perform reliably under real workloads and failures.
• Collaborate with research and inference teams to align infrastructure and model design.
• Track emerging hardware, interconnects, and systems research to guide technical direction.

Requirements

• PhD completed within the last six months or expected by December 2026 in computer science, computer engineering, electrical engineering, or a related field.
• Research experience in distributed systems, operating systems, scheduling, storage, computer networks, computer architecture, or high-performance computing.
• Deep expertise in at least one area: scheduling and resource management, distributed storage and caching, or datacenter networking.
• Strong systems programming skills in C/C++, Rust, Go, or a similar language, plus working proficiency in Python.
• Experience building and evaluating real systems with rigorous performance measurement.
• Ability to communicate system designs and results clearly to diverse audiences.

Nice to have

• First-authored publications at leading systems or networking venues.
• Infrastructure, cloud, or HPC internships, or open-source contributions to systems projects.
• Experience with GPU clusters, CUDA, ROCm, Triton, Kubernetes, cloud infrastructure, or multi-tenant production clusters.
• Experience with distributed performance profiling and debugging.
• Research or engineering achievements demonstrated through grants, fellowships, patents, or systems competitions.

Culture & Benefits

• Work on AI infrastructure problems involving low-latency inference and scalable model serving.
• Collaborate with experienced engineers and AI researchers.
• Receive mentorship from a senior engineer and take ownership of a real systems problem from the start.
• Start dates can be coordinated around thesis defense timelines.
• Operate in a fast-growing environment focused on technical ownership and direct impact.