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7 дней назад

Technical Leader (AI/ML)

250 000 - 350 000$
Формат работы
onsite
Тип работы
fulltime
Грейд
lead
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Technical Leader (AI/ML): Building matching, ranking, retrieval, and agentic systems for an AI recruiting marketplace with an accent on production ML, model evaluation, trust and safety, and quality-cost-latency tradeoffs. Focus on leading an applied AI and ML engineering pod, solving difficult modeling and cold-start problems, and shipping production code while setting technical direction.

Location: San Francisco, United States

Salary: $250,000–$350,000 per year plus equity

Company

hirify.global is an end-to-end AI recruiting marketplace connecting companies with specialized recruiters and AI agents to fill roles faster and more accurately.

What you will do

  • Own the AI Platform engineering team and set technical direction for matching, ranking, retrieval, personalization, and agentic systems.
  • Hire, coach, and level a pod of Applied AI, ML, and Product engineers working in small autonomous teams.
  • Stay hands-on by designing data and labeling strategies, features and embeddings, model selection, training, fine-tuning, and production systems.
  • Solve difficult modeling problems including ranking plateaus, conflicting offline and production evaluations, and cold-start scenarios.
  • Build evaluation frameworks for model quality, reliability, and business impact, and turn ambiguous goals into quarterly plans.
  • Balance model capability, system quality, cost, and latency while improving automation, match quality, and hiring velocity.

Requirements

  • Staff-level individual-contributor depth in ML or applied AI while leading technical work.
  • At least 1 year of managing or formally tech-leading engineers, or 4+ years setting technical direction across multiple teams.
  • Production experience shipping ML or LLM systems used at scale, including retrieval, ranking, recommendation, or agentic workflows.
  • Strong evaluation and data skills, including measuring model quality against business outcomes, using SQL, and assessing experiments.
  • Comfort using AI tools, writing decision documents and postmortems, and shipping production code every week.

Culture & Benefits

  • Small autonomous teams with high expectations for judgment.
  • Promotion is based on judgment and impact rather than lines of code.
  • The role offers meaningful ownership while the engineering organization is scaling.
  • Equity is included in the compensation package.

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