ML Performance Optimization Software Engineer (AI)

TL;DR

ML Performance Optimization Software Engineer (AI): Leading a multi-disciplinary team to evolve the software side of hardware-software co-design projects for machine learning acceleration, with an accent on numerics, performance optimisation, and novel model architecture exploration. Focus on defining strategy for next-generation ML accelerators, managing technical execution, and delivering high-quality solutions on tight schedules.

Location: Onsite in New York City, New York, US

Company

hirify.global is a team of scientists, engineers, and machine learning experts advancing the state of the art in artificial intelligence for widespread public benefit and scientific discovery.

What you will do

• Lead multi-disciplinary ML software engineers focusing on numerics, performance optimisation, and model architecture.
• Collaborate with the hardware team to define strategy for next-generation ML accelerators.
• Manage technical execution and relationships across virtual teams and external partners.
• Drive the team to deliver high-quality solutions aligned with tight schedules.

Requirements

• Bachelor's degree in Electrical Engineering, Computer Science, or equivalent practical experience.
• 10+ years of experience in ASIC design and development.
• Proven track record of technical leadership and successfully delivering complex silicon projects to production.
• Deep expertise in at least one core silicon discipline (e.g., RTL, PD, DV) and strong familiarity with the entire ASIC flow.
• Experience with managing silicon vendors and other external partners.

Nice to have

• Master's or Ph.D. in a related field.
• Experience leading and managing teams across the full silicon development cycle, from RTL to bringup.
• Experience with high-performance compute IPs (e.g., GPUs, ML accelerators).
• Knowledge of high-performance and low-power architectures for ML acceleration.
• Excellent communication and leadership skills.

Culture & Benefits

• Foster a unique culture and work environment where long-term ambitious research can flourish.
• Value strong leadership, technical depth, and a collaborative spirit.
• Encourage flexibility and adaptability to invent novel solutions to problems.