Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Зарплата и рынок
Выше среднего
$144к/год
$76к$110кмедиана$170к
По похожим ролям (50) ~ $110к/год
Прикинули из $12к/мес × 12
На СНГ рынке: $4.8к/мес ($3.6к - $6.5к)
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Роль лида четко описана, а сочетание ML и количественных исследований, заявленная зарплата и доля от PnL выглядят привлекательно. При этом условия бонуса и ограниченная информация о компании оставляют вопросы о полном доходе и стабильности команды.
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Условия бонусаСовременный стекХорошая базовая зарплатаВлияние на исследованияРискованный сектор
Оценка от Hirify AI
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
ML Lead (Quantitative Trading): Developing and improving ML-driven trading strategies, quantitative models, and research pipelines for forecasting and signal generation with an accent on time-series analysis, market data, and statistical modeling. Focus on validating trading hypotheses, optimizing algorithm speed, and bringing profitable strategies into production-ready state.
Location: Remote setup with flexible hours
Salary: Up to $12,000 net per month plus a 4–10% PnL share, negotiated individually
Company
hirify.global is a low-bureaucracy quantitative trading team with a main office in Serbia and a distributed team.
What you will do
Develop and improve algorithmic trading strategies.
Build machine learning and quantitative models for forecasting and signal generation.
Analyze time-series and real-time market data.
Generate, test, and validate hypotheses, signals, and models.
Optimize algorithm speed and efficiency and work with research and backtesting infrastructure.
Help establish new directions and potentially grow a research team.
Requirements
Senior or lead-level experience in ML-driven trading or quantitative research.
Proven experience developing profitable trading or machine learning-driven strategies.
Strong Python and machine learning skills, including NumPy, Numba, PyTorch or JAX, and scikit-learn.
Strong mathematical and statistical background with experience working with time-series and market data.
Experience building, testing, and validating trading hypotheses, signals, and models.
Understanding of trading principles, market structure, and market data.
Nice to have
Ability to read, analyze, and optimize C++ code.
Experience with production machine learning systems, HFT, arbitrage, market-making, or low-latency systems.
Competitive programming or a strong academic background, including ICPC, Kaggle, or Yandex SHAD.
Publications at top-tier machine learning conferences or strong results in ML, data science, or quantitative competitions.
Experience developing complex machine learning and deep learning models.
Culture & Benefits
Small, low-bureaucracy team with fast decision-making.
Rapid hypothesis testing and a research-focused working environment.
Distributed team with a main office in Serbia.
Remote work and flexible hours.
Performance-based PnL share of 4–10%.
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