Distributed Compute Developer

My client is a top-tier algorithmic trading firm, and their research cluster sits at the core of everything they do. This environment is where trading ideas are developed, tested, and pushed into production at scale.

They’ve built a highly customized research platform with cutting-edge CPU and GPU compute, high-performance storage, and low-latency networking. The team works across the full software stack — from user-facing APIs to deep system-level performance tuning — solving problems that range from fair resource scheduling to squeezing every last millisecond out of research workloads.

They’re looking for a Distributed Compute Engineer to help evolve this platform and make research faster, more efficient, and easier for users. This is a highly user-facing role with constant collaboration alongside quantitative researchers and engineers across trading teams.

What you’ll do

• Own and improve the research compute environment with a strong focus on real user workloads
• Build and optimize systems for resource scheduling, data caching, and job monitoring
• Speed up researcher iteration by optimizing workloads at both the user and infrastructure level
• Provide clear metrics and real-time visibility into workload behavior
• Work directly with researchers to understand their needs and turn them into technical solutions
• Help set the technical direction of the platform and take end-to-end ownership of core infrastructure

What they’re looking for

• Bachelor’s degree in Computer Science, Computer Engineering, or a related field
• Strong C++ experience (used regularly in production)
• Python experience is a plus
• Experience partnering closely with quantitative researchers or traders
• Strong communication skills and the ability to work in a user-facing engineering role
• Excellent system design, debugging, and problem-solving skills
• Solid understanding of Linux/UNIX systems, performance optimization, and networking