AI Infrastructure Engineer

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.

As an AI Infrastructure Engineer at DRW, you will be an integral member of a collaborative research team solving the financial markets using machine learning. You’ll work on high-impact machine learning (ML) and artificial intelligence (AI) projects central to our core business. In this role, you will build, maintain and optimize training and inference infrastructure to support researcher to build AI models for financial markets and discover innovative methods to challenging data and machine learning technical problems.

Key Responsibilities:

• Drive end-to-end development of data and AI infrastructure: from initial proof-of-concept to production deployment and ongoing maintenance.
• Provide technical leadership in selecting, integrating, and optimizing AI and ML frameworks, libraries, and tools across diverse hardware and software environments.
• Maintain, and optimize training infra stack, including data pipeline, GPU utilization, monitoring, and observability.
• Proactively troubleshoot performance bottlenecks, conduct root-cause analyses, and implement solutions to optimize GPU or CPU resource usage for both training and inference.
• Design and implement strategies for efficient data movement between storage and GPUs, ensuring high throughput and low latency.
• Develop and maintain high-performance data loading and preprocessing pipelines that maximize GPU utilization.
• Optimize data access patterns and memory management to improve the efficiency of large dataset processing.
• Architect solutions for handling vast volumes of data, ensuring scalability and performance.

Qualifications:

• 3+ years with demonstrated experience in optimizing data movement and processing for GPU-based systems.
• Expertise in GPU memory management and data transfer optimization.
• Experience with GPU-accelerated libraries like RAPIDS
• Skills in developing high-performance data loading and preprocessing pipelines with tools like DALI.
• Skills in profiling and optimizing GPU code using tools like NVIDIA Nsight and nvprof.
• Knowledge of distributed computing frameworks and multi-GPU setups.
• Knowledge of distributed training frameworks like DeepSpeed. Prior experience in scaling neural network training and multi-GPU experiments is preferred.
• Some proficiency in CUDA/Triton programming and CUDA kernels optimization is preferred.
• Proficient in problem-solving and analytical reasoning.
• Exceptional communication and collaboration skills.

The annual base salary range for this position is $130,000 to $200,000, depending on the candidate’s experience, qualifications, and relevant skill set. The position is also eligible for an annual discretionary bonus.  In addition, DRW offers a comprehensive suite of employee benefits including group medical, pharmacy, dental and vision insurance, 401k (with discretionary employer match), short and long-term disability, life and AD&D insurance, health savings accounts, and flexible spending accounts.

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