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Machine Learning Engineer / Quant Developer (C++ & Python) – Global Proprietary Trading Firm – [.]
Our client is a leading global proprietary trading firm with one of the world's strongest quantitative research platforms.
They are expanding a specialist team in Hong Kong that develops the machine learning infrastructure powering multiple systematic trading teams globally.
Rather than working on a single trading strategy, you'll build scalable research tools, frameworks and machine learning capabilities that are used by multiple profitable quantitative investment teams across the firm.
This is a rare opportunity to work on cutting-edge machine learning engineering problems in an environment where research directly impacts live trading.
What You'll Do
Build and optimise machine learning and deep learning infrastructure for quantitative research.
Develop high-performance research frameworks and production-ready tooling.
Partner closely with quantitative researchers to accelerate model development and experimentation.
Design scalable data processing and model training pipelines.
Write performance-critical software in Python and C++.
Contribute to the architecture of next-generation research platforms used across multiple trading teams.
What We're Looking For
Strong software engineering fundamentals with excellent coding ability.
Background in machine learning, deep learning, AI, quantitative research, or research engineering.
Excellent academic record in Computer Science, Mathematics, Statistics, Physics, Engineering or a related quantitative discipline.
Typically 2-7 years' experience, although exceptional candidates at any level will be considered.
Experience from either finance or leading technology companies is welcome.
Mandarin language skills are highly advantageous.
Why Join
Join one of the world's most respected proprietary trading firms.
Work alongside world-class quantitative researchers and engineers.
Solve challenging machine learning and distributed systems problems at scale.
Research-driven environment with direct impact on live trading.
Exceptional compensation and career progression.
Based in Hong Kong.
#J-18808-Ljbffr
or continue with email
They are expanding a specialist team in Hong Kong that develops the machine learning infrastructure powering multiple systematic trading teams globally.
Rather than working on a single trading strategy, you'll build scalable research tools, frameworks and machine learning capabilities that are used by multiple profitable quantitative investment teams across the firm.
This is a rare opportunity to work on cutting-edge machine learning engineering problems in an environment where research directly impacts live trading.
What You'll Do
Build and optimise machine learning and deep learning infrastructure for quantitative research.
Develop high-performance research frameworks and production-ready tooling.
Partner closely with quantitative researchers to accelerate model development and experimentation.
Design scalable data processing and model training pipelines.
Write performance-critical software in Python and C++.
Contribute to the architecture of next-generation research platforms used across multiple trading teams.
What We're Looking For
Strong software engineering fundamentals with excellent coding ability.
Background in machine learning, deep learning, AI, quantitative research, or research engineering.
Excellent academic record in Computer Science, Mathematics, Statistics, Physics, Engineering or a related quantitative discipline.
Typically 2-7 years' experience, although exceptional candidates at any level will be considered.
Experience from either finance or leading technology companies is welcome.
Mandarin language skills are highly advantageous.
Why Join
Join one of the world's most respected proprietary trading firms.
Work alongside world-class quantitative researchers and engineers.
Solve challenging machine learning and distributed systems problems at scale.
Research-driven environment with direct impact on live trading.
Exceptional compensation and career progression.
Based in Hong Kong.
#J-18808-Ljbffr
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