aisqlllmmachine learningstartupretrievalrankingtrust and safetyagentic systems
Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Зарплата и рынок
Выше среднего
$250к-350к/год
$210к$250кмедиана$300к
По похожим ролям (49) ~ $250к/год
На СНГ рынке: $5.3к/мес ($3.8к - $7.4к)
90
Крутая вакансия
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Высокая зарплата, понятная техническая зона ответственности и руководство разработкой AI-систем делают роль перспективной, но в быстрорастущем стартапе объём ответственности может быть большим.
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Широкая зона ответственностиЗарплата выше рынкаAI в основе продуктаБыстрый рост
Оценка от Hirify AI
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Описание вакансии
Текст:
Hirify AI/Оригинал
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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