Senior System Software Engineer

At Chicago UpDown (https://www.chupdown.com/), we are building breakthrough graph computing acceleration - software and hardware.  With 1000x performance of today's cloud-based approaches, UpDown enables instant real-time mapping and analytics of trillion-node graphs.  The core technologies were created as part of IARPA's AGILE program, and spun out from the University of Chicago and Purdue University.

We are looking for a talented System Software engineer, experienced with Linux and HPC, and capable with advanced AI tools to lead the design and enhancement of system software for a sophisticated, scalable global memory management and scale-out parallel cluster system (>10,000 nodes).

We are seeking a talented System Software Engineer to design, build, and optimize the memory and system software stack for our scalable, accelerator-based global memory system, UpDown.

Challenges include accelerator global memory (petabytes of unified virtual memory) and resource management in large-scale parallel systems (cloud and HPC-like).  The technical challenges exceed the largest cloud and HPC systems today.

Key Responsibilities

• Lead the design and implementation of a petabyte-scale unified virtual memory system to leverage novel hardware translation features and capabilities.
• Global Memory and system library: System and application allocators & runtimes, including custom memory allocators and system-level runtime infrastructure to maximize throughput.
• Task/Job Scheduling & Orchestration: Integrate and optimize HPC workload managers and job scheduling systems (such as Slurm, PBS, or custom schedulers) to efficiently allocate resources and orchestrate massively parallel jobs.
• Kernel and Driver Engineering: Linux kernel and driver work to support and optimize the memory management and device driver subsystem, develop custom modules, and eliminate kernel-space bottlenecks.

Minimum Qualifications

• Education: Master’s or Ph.D. in CS, CE, or related field.
• Systems Programming Experience: 3+ years of hands-on experience writing production-grade, low-level code in C and C++ and/or Linux kernel programming.
• Virtual and Memory Management Knowledge: Deep understanding of OS-level memory management, virtual memory, paging, and custom memory allocators.
• Parallel Computing or HPC Experience: 3+ years in HPC/Cloud scalable systems software, writing/modifying software for HPC, supercomputer, and accelerator environments.

Preferred Qualifications

• 5+ years hands-on experience developing or modifying OS kernels (Linux), hypervisors, or low-level runtime libraries.
• Strong understanding of the challenges associated with memory management in multi-tenant, globally distributed cloud infrastructure.
• Advanced Interconnects: Demonstrated experience working with high-performance network and memory fabrics, such as RDMA (RoCE, InfiniBand), CXL, and NVLink.
• Experience with graph workloads and algorithms (e.g., Graph500 BFS) on modern hardware.

To apply, send a cover letter and resume to [email protected]

About Chicago UpDown Computing

Chicago UpDown Computing, Inc. is creating accelerated computing for scalable, real-time graph analytics in the government intelligence, financial fraud, graphRAG, and network cybersecurity markets.   With single-node demonstrated performance of 100x times that of CPU/GPU systems, scaling to 1000x and UpDown exploits massive thread and memory parallelism to achieve breakthrough performance.

UpDown is a spinout from the University of Chicago and Purdue, capitalizing on 4 years of US Government Intelligence ARPA (IARPA) funded research.  While Chicago UpDown is in stealth mode, https://www.chupdown.com/ technical information on the IARPA project is available from http://updown.cs.uchicago.edu/