Distributed Compute Technical Lead
Cumberland
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 a Distributed Compute Technical Lead at DRW, you will lead the design and evolution of the distributed computing platforms that power our research, trading, and analytics workloads. You’ll define the technical direction for how teams build, scale, and interact with DRW’s compute resources, making complex infrastructure approachable and efficient for developers, quants, and traders alike. Acting as a bridge between systems engineering, software development, and end-user enablement, you will play a pivotal role in shaping the next generation of our compute ecosystem.
Key Responsibilities
- Architect and evolve DRW’s distributed compute platforms to support current and emerging workload types across trading, research, and analytics.
- Develop abstractions, APIs, and developer libraries that simplify job orchestration, data movement, and distributed execution for end users.
- Collaborate with system and infrastructure engineers to optimize scheduler configurations, cluster performance, and resource utilization.
- Partner with application developers, quants, and traders to understand computational requirements and translate them into scalable, user-friendly solutions.
- Drive modernization initiatives around containerization, orchestration, and hybrid compute strategies to enable future workloads.
- Establish best practices and governance for distributed workload design, reproducibility, and reliability.
- Mentor engineers and guide teams in distributed systems architecture, performance tuning, and platform design.
- Champion user experience improvements, making the platform intuitive for all technical levels through tools, templates, and clear documentation.
- Evaluate emerging technologies and frameworks that advance distributed computing, workflow orchestration, and data-driven research efficiency.
Qualifications
- Bachelor’s or advanced degree in Computer Science, Engineering, or a related field.
- 7+ years of combined experience in architecting and operating distributed or high-performance computing systems at scale.
- Strong programming skills in Python, C++, or similar languages, with a focus on building APIs or libraries that abstract infrastructure complexity.
- Deep knowledge of workload schedulers and orchestration platforms (e.g., Slurm, LSF, HTCondor).
- Experience driving cross-functional projects that span infrastructure and software development teams.
- Proven ability to enhance developer experience and usability for complex distributed systems.
- Excellent communication and collaboration skills, with the ability to influence across technical domains and user groups.
- Familiarity with compute workloads common in financial, scientific, or ML research environments.
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