High Performance Data & Algorithm Infrastructure Engineer
Location: San Diego, CA
Job Type: Full-Time
$175k - $185k, bonus, equity
Position Overview
We are a startup building performance-critical systems that push large volumes of data through tightly optimized compute pipelines. We are looking for a Senior Staff Software Engineer with deep expertise in high-performance computing (HPC), Linux systems, and GPU-accelerated data pipelines.
This is a highly technical, hands-on role focused on extracting maximum performance from modern CPUs, GPUs, memory subsystems, and high-speed networks. You will work close to the hardware and operating system, tuning kernels, BIOS settings, and drivers, while also designing and implementing low-latency data processing pipelines that include real-time signal processing.
If you enjoy profiling, tuning, and eliminating bottlenecks across the full stack—from BIOS to CUDA kernels to network offload—this role is for you.
Key Responsibilities
High-Performance System Engineering
- Design, build, and optimize high-throughput, low-latency compute pipelines
- Profile and tune performance across CPUs, GPUs, memory, storage, and networking
- Identify and eliminate bottlenecks in data movement and computation
- Work directly with hardware and OS configuration to achieve deterministic, repeatable performance
Linux Systems & Kernel Expertise
- Configure and tune Linux systems for high-performance workloads
- Customize and tune Linux kernel parameters (scheduler, NUMA, IRQs, huge pages, IOMMU, etc.)
- Tune CPU and BIOS parameters (power states, frequency scaling, SMT, NUMA, memory timing)
- Manage and optimize DMA paths between devices and system memory
- Minimize context switches, cache misses, and system jitter
GPU & CUDA Programming (Critical)
- Develop and optimize GPU-accelerated compute pipelines using CUDA
- Optimize memory transfers between host and GPU (pinned memory, zero-copy, GPUDirect where applicable)
- Tune kernel launches, memory access patterns, and occupancy
- Configure and manage GPU drivers, runtime, and system-level settings for maximum throughput
- Profile GPU workloads using tools such as Nsight Systems and Nsight Compute
Data Movement & Networking
- Optimize high-speed data ingestion and offload to HPC systems
- Work with low-latency and high-bandwidth networking technologies (e.g., RDMA, InfiniBand, high-speed Ethernet)
- Minimize data transfer latencies across network, PCIe, and memory boundaries
- Design zero-copy or near-zero-copy data paths where possible
Signal Processing & Algorithms
- Implement and optimize digital signal processing algorithms, including:
- FFTs
- Deconvolution
- Thresholding and detection algorithms
- Optimize DSP workloads for CPU vectorization and GPU acceleration
- Balance numerical accuracy, latency, and throughput constraints
Qualifications
Education:
- BS/MS Computer Science or Engineering
Required:
Experience & Technical Skills
- 7+ years of professional software engineering experience (or equivalent depth)
- Strong background in high-performance computing or performance-critical systems
- Expert-level Linux experience, including kernel and system tuning
- Deep experience with GPU computing and CUDA (required)
- Strong systems programming skills in C/C++ (and/or Rust)
- Solid understanding of computer architecture:
- CPU caches, NUMA, memory hierarchies
- PCIe and DMA
- GPU architectures
Performance & Debugging Skills
- Extensive experience profiling and tuning complex systems
- Comfortable using tools such as perf, ftrace, eBPF, valgrind, Nsight, and similar
- Ability to reason quantitatively about latency, bandwidth, and throughput
DSP & Mathematical Foundations
- Practical experience implementing DSP algorithms in production systems
- Strong understanding of FFTs, convolution/deconvolution, filtering, and thresholding
- Ability to optimize numerical algorithms for real-time or near-real-time constraints
Preferred:
- Experience with RDMA, GPUDirect RDMA, or other hardware offload technologies
- Experience with custom kernel builds or kernel module development
- Familiarity with real-time or low-latency Linux variants
- Experience deploying HPC workloads at scale
- Background in scientific computing, signal processing, or computational physics
What Success Looks Like
- Data pipelines consistently hit performance targets with headroom
- Latency and throughput are predictable, measurable, and well understood
- GPUs and CPUs are efficiently utilized with minimal idle time
- System-level bottlenecks are identified early and resolved decisively
Why This Role is Interesting
- You will work on problems where performance truly matters
- You will operate across the full stack, from BIOS and kernel settings to CUDA kernels and DSP algorithms
- Your optimizations will have immediate, measurable impact
- You will have the freedom to deeply understand and tune the system, not just work around it
Why Join Us
- Influence the foundational technologies and strategies of a company poised to shape the future of clinical genomics and healthcare.
- Work in a dynamic, collaborative environment where innovation and scientific rigor are deeply valued.
- Join a seasoned and multidisciplinary team tackling high-impact problems at the intersection of science and engineering.
- Competitive compensation and equity package, comprehensive benefits, and flexibility to support work-life integration.
If you enjoy building orchestration layers for real machines and solving hard distributed real-time problems, this role offers significant technical ownership and impact.
We are an equal opportunity employer. We thrive on diversity and collaboration.
Compensation Range: $175K - $185K
US
