Machine Learning Researcher

DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world.  We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk. 

Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets. 

We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it.  DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus.  

Our team works on a variety of high-impact machine learning projects with a DRW trading desk, and we are looking for a Machine learning quantitative researcher to join us. In this role you will design, implement and deploy critical systems for our machine learning models and have the chance to make great impact to our business. The role blends software engineering, machine learning, quantitative research and market intuition. As a member of our team, you will be surrounded by cutting-edge technology and experienced machine learning and software professionals providing you with the best possible environment to succeed. You will always have interesting new projects to apply your skillset while also becoming an expert on certain areas.

Responsibilities:

• Research, design and implement scalable and performant systems to serve machine learning models
• Own the full model lifecycle: from idea to production and ongoing performance monitoring
• Optimize training and inference performance of machine learning models
• Optimize models for deployment on different hardware configurations
• Drive projects and lead new initiatives
• Facilitate discussions on code implementation, testing and software architecture
• Actively engage with others on the team to resolve challenging design and coding issues
• Collaborate with stakeholders from different departments

Qualifications:

• Advanced degree (preferably PhD) in computer science, mathematics, physics, software engineering or equivalent
• 4+ years of experience building software for machine learning systems
• Strong background in probability, statistics and information theory
• Deep understanding of machine learning algorithms
• Strong experience in writing clean, modular, efficient and testable code
• Experience with building, validating, deploying, monitoring, and updating production models
• Experience with infrastructure and tooling for MLOps
• Strong problem-solving and analytical skills
• Excellent communication and collaboration skills
• Ability to learn quickly and provide solutions in a high pressure environment
• Experience with GPU programming using CUDA, OpenCL or similar libraries
• Experience with one or more of the following is an asset: distributed systems, multi-threaded programming, hardware/software interaction

What DRW Montreal has to offer you:

• Recognized as one of Canada’s Best Employers for the past 8 years
• Committed to continuous learning & development
• Industry leading benefits package and perks
• Focused on employee well-being and work-life balance
• Community initiatives, volunteer program and opportunities for giving back

Find out more about all of our perks & benefits at: https://drw.com/work-at-drw/montreal-benefits

If you are an experienced software developer who is passionate about machine learning and enjoys working with cutting-edge technologies and solving complex problems, we encourage you to apply for this exciting position. You will have the opportunity to work with a talented and dedicated team to create innovative solutions that can make a significant impact to our business.

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