AI Algorithm Engineer (Hardware Co-Design)

Location: Hybrid (New York City, San Francisco, London, Copenhagen, Pangyo)

Compensation: $200,000 – $400,000 + Equity

Company

hirify.global is an applied AI company building foundational hardware and software for the semiconductor industry and critical AI infrastructure.

What you will do

• Develop algorithms for transformer inference workloads running on stochastic analog processing-with-memory hardware.
• Collaborate with hardware and architecture teams to shape native chip computation.
• Design numerical methods that exploit thermal noise and analog dynamics.
• Build evaluation frameworks and benchmarks to characterize algorithm behavior on real silicon or simulation.
• Translate model workload insights into hardware design constraints and opportunities.

Requirements

• Deep understanding of large model inference including attention mechanisms, KV cache, and long-context decoding.
• Experience with inference optimization techniques such as quantization, sparsity, or kernel fusion.
• Familiarity with stochastic systems, probabilistic methods, numerical analysis, or analog computation.
• Strong programming skills in Python and at least one systems language.
• Track record of taking ideas from theory to working implementation on real hardware.
• Ability to reason from first principles about novel substrate efficiency.

Nice to have

• PhD in machine learning, applied mathematics, physics, electrical engineering, or a related field.
• Exposure to analog or mixed-signal systems, in-memory compute, or non-von-Neumann architectures.
• Experience working on hardware that did not yet exist upon joining.
• Publications or open-source work in efficient inference or stochastic algorithms.

Culture & Benefits

• Competitive and equitable compensation packages including equity.
• Opportunity to work on cutting-edge thermodynamic hardware and co-design roles.
• Collaborative environment working across hardware, architecture, and software teams.
• Commitment to diversity and inclusive workplace practices.