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Applied ML Director (AI)

178 500 - 331 500$
Тип работы
fulltime
Грейд
director
Английский
b2
Страна
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 ML Director (AI): Building and leading production-grade AI agents, evaluation frameworks, data pipelines, and retrieval systems for semiconductor design workflows with an accent on scalable ML infrastructure, LLM deployment, and agent architecture. Focus on designing reliable AI systems, optimizing latency and cost, and leading a team of ML and software engineers while remaining hands-on with architecture and code.

Location: San Jose, California, United States

Annual salary: $178,500–$331,500 in California, plus potential bonus, equity, and benefits.

Company

hirify.global develops electronic design automation software and hardware platforms for designing and verifying semiconductor and intelligent systems.

What you will do

  • Lead, mentor, and grow a team of ML and software engineers.
  • Define the technical vision and contribute hands-on to the ChipStack SuperAgent codebase.
  • Architect production AI agents, evaluation frameworks, data pipelines, RAG systems, and context-engineering strategies.
  • Oversee continuous integration, automated testing, observability, and system performance across latency, cost, reliability, and scalability.
  • Partner with product management, research, and core engineering teams to align the AI roadmap with EDA platform goals.

Requirements

  • MS or PhD in Computer Science, Computer Engineering, or a related technical field.
  • At least 3 years of direct engineering management or formal technical leadership experience.
  • At least 7 years of hands-on software engineering and ML experience.
  • Deep expertise in designing, refactoring, debugging, and testing distributed systems, with current production coding ability.
  • Strong understanding of LLMs in production, including latency, cost, reliability, monitoring, and failure analysis.
  • Experience designing AI evaluation frameworks, benchmarking, and regression testing.

Nice to have

  • Experience with agent architectures, planning and self-correction patterns, tool calling, persistent memory, and structured outputs.
  • Experience with frontier LLMs, prompt engineering, context management, and model alignment.
  • Deep knowledge of RAG pipelines, embeddings, indexing, chunking, and grounding.
  • Experience building ML/AI-specific logging, tracing, monitoring, and evaluation systems.
  • Interest or experience in semiconductor design, EDA workflows, and high-performance computing.

Culture & Benefits

  • Culture of technical excellence, collaboration, continuous learning, and rapid execution.
  • Focus on challenging industry norms while maintaining high quality standards.
  • Paid vacation and paid holidays.
  • 401(k) plan with employer match and employee stock purchase plan.
  • Medical, dental, and vision plan options, plus potential incentive compensation.

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