Optiver is a seeking a Machine Learning Research Engineer to join our team, focusing on a pivotal AI initiative. This role would offer the opportunity to have significant impact across Machine Learning infrastructure, training, and inference challenges to advance our futures trading strategies.
Who we are:
Optiver is a tech-driven trading firm and leading global market maker. As one of the oldest market making institutions, we are a trusted partner of 70+ exchanges across the globe. Our mission is to constantly improve the market by injecting liquidity, providing accurate pricing, increasing transparency and acting as a stabilizing force no matter the market conditions. With a focus on continuous improvement, we participate in the safeguarding of healthy and efficient markets for everyone who participates.
Based in ‘The Domain’ neighborhood, Optiver’s Austin office serves as the firm’s innovation nucleus, with a strong focus on quantitative research, software and hardware engineering initiatives. With tech innovation an integral part of our core business, the booming city proved an ideal backdrop for our heavy investment into machine learning, research infrastructure and big data computing. What’s more, with world-class music, food and art scenes, as well as countless scenic outdoor activities, the quality of life for Austin Optiverians is second to none.
What you'll do:
- Conduct innovative research on deep learning for price forecasting
- Build scalable and robust training and inference pipelines for deep learning
- Dive into internals of open-source deep learning frameworks and enhance their functionality
- Collaborate closely with researchers and other engineers
- Develop an in-depth understanding of trading systems
What you’ll need:
- PhD or equivalent industry experience in a field related to machine learning
- Expertise in building deep-learning models in PyTorch, JAX, or TensorFlow
- Experience in programming in Python
- Experience in computationally intensive research on very large data sets
Nice to have:
- Experience with JAX ecosystem (XLA, Flax, etc.)
- Experience in programming for GPUs or other accelerators (CUDA, Triton, Pallas, etc.)
- Contributions to open-source projects related to data science and machine learning
- Strong publication record at conferences like NeurIPS, ICML, etc.
- Expertise in internals of deep-learning frameworks like PyTorch, JAX, TensorFlow, etc.
- Experience with large-scale distributed training
- Experience in programming in C++
What you’ll get:
- Work alongside best-in-class professionals from over 40 different countries.
- Performance based bonus structure that is unmatched anywhere in the industry. We combine our profits across desks, teams and offices into a global profit pool fostering a truly collaborative environment to work in.
- Ownership over initiatives that directly solve business problems.
Alongside this you will get great other benefits such as 25 paid vacation days and market holidays, fully paid health insurance, daily breakfast and lunch, training opportunities, 401(k) match up to 50% and charitable match opportunities, regular social events and clubs, and many more.
At Optiver, we are committed to creating a diverse and inclusive environment of mutual respect. Optiver recruits, employs, trains, compensates and promotes regardless of race, religion, color, sex, gender identity, sexual orientation, age, physical or mental disability, or other legally protected characteristics.
Top Skills
What We Do
Optiver’s story began over 30 years ago, when we started business as a single trader on the floor of Amsterdam’s options exchange. Today, we are at the forefront of trading and technology as a leading global electronic market maker, focused on pricing, execution and risk management.
Why Work With Us
People at Optiver love challenges, welcome collaboration, and strive to be better tomorrow than they are today. Improving the market is an extraordinary challenge that requires a carefully crafted approach. Optiver provides a collaborative working environment to tackle these challenges. In fact, it is this way of working that sets us apart.