As a Machine Learning Modelling Engineer, you’ll harness your understanding of AI and deep learning to generate impactful insights and drive innovative new strategies that have the potential to transform global financial markets.
Your intellectual creativity won’t just be theoretical; you’ll get to turn your cutting-edge ideas into real-world solutions that contribute towards our trading success.
You’ll join a team of experienced engineers, who will provide you with guidance and support throughout the program, enabling you to make an impact from the early stages of your Optiver career.
By the end of the internship, you'll have deepened your understanding of the quantitative trading industry. Plus, if you've excelled over the summer, you'll receive an offer to return as Graduate Machine Learning Modelling Engineer.
WHAT YOU’LL DO:
During the internship, you will have the opportunity to:
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Leverage AI and deep learning technologies to thrive in a fast-paced, innovative environment.
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Collaborate closely with researchers and traders on new experiments, capabilities and data sources.
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Design and implement improvements to optimise researcher productivity and quality.
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Blend your own development expertise with the best open-source frameworks and tools.
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Utilise computing infrastructure to solve substantial challenges in computational and data scale.
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Drive experimental rigour through repeatable processes on assured data.
WHAT YOU'LL GET:
You’ll join a culture of collaboration and excellence, where you’ll be surrounded by curious thinkers and creative problem solvers. Driven by a passion for continuous improvement, you’ll thrive in a supportive, high-performing environment alongside talented colleagues, working collectively to tackle the most complex problems in the financial markets.
In addition, you’ll receive:
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A highly competitive remuneration package.
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Optiver-covered flights and accommodation for the duration of the internship.
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The opportunity to work alongside best-in-class professionals.
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Training, mentorship and personal development opportunities.
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Gym membership, plus weekly in-house chair massages.
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Daily breakfast, lunch and in-house barista.
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Regular social events.
WHO YOU ARE:
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PhD students who are graduating in or after 2027.
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Studying a degree in Computer Science, Mathematics, Statistics, or a related field, with a strong focus on machine learning or deep learning.
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You’ll have an advanced understanding of neural networks and related machine learning technologies, with experience in implementing and training complex deep learning models.
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Proven experience with deep learning frameworks such as TensorFlow, PyTorch, Keras, etc.
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Deep understanding of the principles, theories and concepts underlying machine learning and deep learning technologies, including the design and implementation of neural networks.
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Strong programming skills in Python, familiar with data engineering tools and principles.
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Experience with GPUs and other hardware accelerators for deep learning.
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Excellent problem-solving skills, and the ability to work independently and in teams.
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Outstanding communication skills.
HOW TO APPLY
If you're ready to take the next step in your career and work on one of the most exciting trading floors in mainland China, we’d love to hear from you. Apply now via the form below.
In your application, please submit the following materials in English:
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Resume
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Cover letter (optional)
For any other inquiries, contact us at chinacareers@optiver.com.au
DIVERSITY STATEMENT
Optiver is committed to diversity and inclusion. We encourage applications from candidates of all backgrounds, and welcome requests for reasonable adjustments during the process.
We accept one application per role per year. If you have previously applied to this position during this season and have been unsuccessful, you can re-apply when the next recruitment season begins in 2027.
PRIVACY DISCLAIMER
Optiver 重视个人信息的保护。请您在提供个人信息给我们之前，认真阅读Optiver China Privacy Notice, 了解我们如何收集及处理您的个人信息。
Personal information protection is of utmost importance to Optiver. Before you provide any personal information to us, we strongly urge you to read our Privacy Policy to acknowledge how we collect and process your personal information.