Machine Learning Engineer

at  DRW

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 across DRW’s businesses, and we are looking for a Machine learning engineer to join us. In this role you will build critical systems for our machine learning models and have the chance to make great impact to our business. As a member of our team, you will be surrounded by cutting-edge technology and experienced machine learning, data 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.

QUALIFICATIONS:

• A bachelor’s or a master’s degree in computer science, software engineering or equivalent
• 6+ years of experience building software for machine learning systems
• Strong understanding of machine learning and deep learning concepts
• Excellent programming and scripting skills (we predominantly work in Python and Go)
• 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
• Experience with machine learning frameworks such as TensorFlow, PyTorch, TensorRT, ONNX
• Experience with GPU programming using CUDA, OpenCL or similar libraries
• Experience with one or more of the following is an asset: distributed systems and cloud computing (Kubernetes, Docker, GCP, AWS), multi-threaded programming, hardware/software interaction

• Design and implement scalable and performant systems to serve machine learning models
• Optimize training and inference performance of deep learning models
• Create and maintain feature pipelines, feature stores, model stores
• Monitor production models and setup retraining infrastructure to improve performance
• Optimize models for deployment on different hardware configurations
• Build frameworks to promote scalable and reproducible research
• Drive projects and lead new initiatives
• Facilitate discussions on code implementation, testing, software architecture best practices
• Actively engage with others on the team to resolve challenging design and coding issues
• Collaborate with stakeholders from different departments