Senior Machine Learning Engineer
Summary
Build and deploy production AI systems for a quantitative trading firm, designing ML models, pipelines, and infrastructure to support trading workflows.
Senior Machine Learning Engineer/ML Research Engineer - Hong Kong - Open Budget
*finance domain experience not required*
We're partnering with a leading quantitative trading firm to hire a Senior Machine Learning Engineer/ML Research Engineer to build the next generation of production AI systems that support real-world trading and research workflows.
Salary: open budget - willing to pay for the right candidates.
This is an opportunity to work at the intersection of machine learning research, large-scale engineering, and high-performance systems, taking models from experimentation through to production in a fast-paced, highly technical environment.
What you'll be doing
- Design, train and deploy production machine learning models.
- Build scalable data pipelines, model training infrastructure and inference systems.
- Develop end-to-end ML workflows covering data processing, training, evaluation, deployment and monitoring.
- Work on large-scale distributed ML systems and optimise model performance for production.
- Collaborate closely with researchers and engineers to turn cutting-edge ideas into robust, production-ready solutions.
- Contribute to the development of AI infrastructure supporting next-generation research initiatives.
What we're looking for
- Strong experience building and deploying production machine learning systems.
- Hands-on experience with Python and modern deep learning frameworks such as PyTorch or TensorFlow.
- Experience developing end-to-end ML pipelines, from data engineering through model serving.
- Background in large-scale model training, distributed computing or inference optimisation.
- Experience with LLMs, multimodal models, reinforcement learning or foundation models is highly desirable.
- Excellent software engineering skills with a passion for solving complex technical problems.
If you're excited by solving challenging machine learning problems at scale and want to see your work deployed in a production environment where performance matters, we'd love to hear from you.