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6 дней назад

Applied Researcher (AI Agents)

150 000 - 300 000$
Формат работы
remote (только USA)
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
UK/US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
Applied Researcher (AI Agents) (Frontier AI/Semiconductor Design): Building agent environments, verifiers, evaluations, and post-training systems for semiconductor design and verification workflows with an accent on reinforcement learning, EDA tools, and long-horizon experimentation. Focus on designing rewards for functional correctness and engineering constraints, debugging multi-tool failures, and evaluating recovery and generalization across designs.

Location: San Francisco, New York, London, or remote

Cash compensation: $150,000–$300,000 annually plus equity incentives

Company

hirify.global is building an open superintelligence stack combining compute, environments, evaluations, secure sandboxes, high-performance training, and deployment for frontier AI research and production.

What you will do

  • Build interactive environments where agents use EDA tools to modify designs, debug failures, and plan multi-step work.
  • Develop verifiers and reward signals grounded in tests, simulation, formal methods, design rules, and engineering outcomes.
  • Run experiments on credit assignment when feedback arrives late and multiple tools contribute to outcomes.
  • Design evaluations for correctness, recovery, and generalization across blocks, designs, and constraint sets.
  • Build agents, environments, evaluations, and post-training systems for RTL generation and debugging, formal verification, simulation, physical design, optimization, and orchestration across EDA tools.
  • Work directly with customers, users, or research partners while maintaining a substantive research agenda.

Requirements

  • Depth in reinforcement learning, agents, or post-training systems, with the ability to become fluent in semiconductor workflows.
  • Hands-on experience building and debugging model-training, post-training, agent, evaluation, or closely adjacent experimental loops.
  • Strong experimental judgment, including meaningful baselines, careful trace inspection, clear failure attribution, and evidence-driven iteration.
  • Strong Python skills and the ability to build artifacts that other researchers and engineers can run, inspect, and extend.
  • Comfort owning ambiguous problems and keeping partners and teammates current while resolving them.

Nice to have

  • Prior work in design automation, compilers, formal methods, or machine learning for systems.
  • Publications, open-source systems, benchmarks, or shipped products demonstrating exceptional work.

Culture & Benefits

  • Flexible work from San Francisco, New York, London, or remotely.
  • Visa sponsorship and relocation support.
  • Professional development budget.
  • Team off-sites and conference attendance.
  • Opportunity to work at the intersection of frontier research, real infrastructure, and customer-facing applied research.

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