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Machine Learning Research Engineer (Machine Learning)

Тип работы
fulltime
Грейд
middle/senior
Английский
b2
Страна
China
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
Machine Learning Research Engineer (Machine Learning): Building and scaling training, inference, and research workflows for machine learning in a trading environment with an accent on mathematical foundations, reproducible research, and production infrastructure. Focus on bridging research and engineering, evaluating modelling approaches, designing workflow APIs, and enabling new scale across the technology stack.

Location: Hong Kong

Company

hirify.global is a financial technology and quantitative trading firm using machine learning as a core part of its global business.

What you will do

  • Build and maintain machine learning training and inference infrastructure from research concepts through production.
  • Enhance research workflows and shorten feedback cycles for machine learning experimentation.
  • Partner with researchers to rapidly prototype new ideas and extend model capabilities across the technology stack.
  • Design workflow APIs and systems supporting a wide range of machine learning use cases.
  • Evaluate modelling approaches including neural networks, random forests, gradient-boosted trees, and ensemble methods.

Requirements

  • Experience building and maintaining training and inference infrastructure.
  • Strong mathematical background, including optimisation theory, regularisation techniques, and linear algebra.
  • Ability to create and maintain organised research codebases with robust, reproducible results.
  • Expertise with an ML framework such as PyTorch, JAX, or TensorFlow.
  • Fluent English and an inventive, questioning approach to technical decisions.

Culture & Benefits

  • Collaborative machine learning team focused on software engineering and usable API and system design.
  • Rapid-feedback trading environment for machine learning experimentation.
  • Opportunities to engage with academic research, new hardware, and emerging machine learning tools.
  • Equal opportunity employment environment.

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