Senior Machine Learning Engineer

Optiver is a global market maker founded in Amsterdam, with offices in London, Chicago, Austin, New York, Sydney, Shanghai, Hong Kong, Singapore, Taipei and Mumbai. Established in 1986, today we are a leading liquidity provider, with over 2,000 employees in offices around the world, united in our commitment to improve the market through competitive pricing, execution and risk management. By providing liquidity on multiple exchanges across the world in various financial instruments we participate in the safeguarding of healthy and efficient markets. We provide liquidity to financial markets using our own capital, at our own risk, trading a wide range of products: listed derivatives, cash equities, ETFs, bonds and foreign currencies.

Since its establishment in 2012, our Shanghai office is a rapidly growing participant in the Chinese markets, trading exchange-listed futures, options and equities in China mainland. Our vision is to become the trusted partner in the development of Chinese financial markets. With the culture of a start-up but the backing of a close-to-40 year-old trading firm, the Optiver Shanghai office is truly unique. Everyone who joins us will help shape the future of our company and its global impact. Get ready: we are only just beginning.

About the AI Lab at Optiver

Optiver has built its reputation as a global leader in trading through rigorous research, rapid innovation, and uncompromising performance. Now, were launching a new frontier: AI Lab Shanghai.

This newly established team will operate independently from our core trading operations, serving as a long-term innovation engine to explore, develop, and apply the most advanced AI and machine learning technologies to complex problems. From foundational model development to novel AI systems, the AI Lab will be at the forefront of pushing boundaries.

Key Responsibilities

• Building the compute platform and machine learning libraries for large scale machine learning and simulation workloads
• Focus on compute platform stability and efficiency on both CPU and GPU clusters, making the platform observable and scalable
• Utilize cluster monitoring and profiling tools to identify bottlenecks and optimize both infrastructure and software system

Challenges You Will Tackle: design, build and improve our compute platform for PB scale data model training and simulations with a wide range of machine learning models by leveraging our existing research infrastructure.

Requirements:

• Solid experience in running production machine learning infrastructure at a large scale
• Experience in designing, deploying, profiling and troubleshooting in Linux-based computing environments
• Proficiency in containerization, parallel computing and distributed training algorithms
• Experience with storage solutions for large scale, cluster-based data intensive workloads

Bonus qualification:

• Experience of supporting machine learning researchers or data scientists for production workloads

Why Join Us?

• Build a new frontier of AI innovation at one of the worlds top trading firms.
• Operate in a high-trust, low-bureaucracy environment with exceptional resources.
• Access to cutting-edge infrastructure, compute, and proprietary datasets.
• Competitive compensation and long-term incentives.

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