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As a Machine Learning Engineer Intern at Optiver, you’ll work alongside experienced engineers on high-performing systems that respond to live financial markets in real time. You’ll contribute to the compute platforms and libraries that support large-scale machine learning model training and simulation workloads, gaining hands-on experience applying modern ML techniques to real quantitative trading problems. Within weeks, you could be building tools or models that run in production and directly support our trading strategies. By the end of the 8-week internship, you’ll have a clear and practical understanding of how technology and ML techniques are used in the quantitative trading industry. Plus, if you’ve excelled over the summer, you’ll receive an offer to return as a Machine Learning Engineer. What you’ll do: Led by our in-house education team that consists of ex-traders and engineers, you’ll delve into advanced engineering concepts and lead innovative projects, during our world-class training program. In just a few weeks, you'll have the opportunity to: Gain first-hand experience applying the latest ML methodologies to quantitative trading problems. Help build the compute platform and libraries for large scale ML model training and simulation workloads. Manage a project end-to-end, learn how to work with a complex code base and make impactful contributions to production systems. Work on real trading and IT problems, both technically and functionally, to improve our trading success. Throughout the program, you'll be paired with an experienced mentor, who will show you the ins-and-outs of our trading systems, and provide you with guidance and feedback. Additionally, internal resources will be available for your continuous learning and development. 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: A highly competitive remuneration package. Optiver-covered flights and accommodation for the duration of the internship. The opportunity to work alongside diverse and intelligent peers in a rewarding environment. Training, mentorship and personal development opportunities. Gym membership, plus weekly in-house chair massages. Daily breakfast, lunch and in-house barista. Regular social events. Who you are: Students graduating in 2028 or later . Foundations in Machine Learning, including optimisation and deep learning concepts. Hands-on experience with deep learning frameworks such as PyTorch, JAX, or similar. Interested in building scalable and reproducible machine learning pipelines, including data preprocessing, training, evaluation, and experiment tracking. Natural problem solvers who love tackling a complex technical challenge. Team players who thrive in collaborative environments and are eager to learn, iterate, and improve. Interested in the trading / quantitative finance industry (prior finance knowledge is not required). Optional: Ability to identify and reason compute and performance bottlenecks, using profiling, benchmarking, and systematic analysis to improve training efficiency. Experience with distributed training or GPU acceleration is a plus. Familiarity with experiment management tools (e.g. MLflow, Weights & Biases) or workflow orchestration is a plus. How to apply: Don’t miss your chance to accelerate your career and thrive on one of the most dynamic trading floors in mainland China. Apply now via the form below. In your application, please submit the following materials in English: Resume Cover letter (optional) Questions? Please email chinacareers@optiver.com.au . 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 . 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. 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.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.