Staff Engineer, High Performance Data & Algorithm Infrasturcture

Staff Engineer, High Performance Data & Algorithm Infrasturcture

Location: San Diego, CA

Job Type: Full-Time

Pay Range: $175k - $185k, bonus, equity

About Us

We are a venture-backed, stealth-stage biotechnology company based in San Diego, focused on developing novel technologies that will redefine how disease is detected, characterized, and managed with a novel approach to clinical genomics. Our mission is to fundamentally transform healthcare through a convergence of innovation across multiple scientific disciplines.

Founded by industry veterans with decades of experience in life sciences tools and diagnostics, our leadership team brings a proven track record of translating scientific insight into successful commercial products. Our investors include some of the most respected names in healthcare and deep tech.

Position Overview

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 in 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

• 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.

Radian is an equal opportunity employer. We thrive on diversity and collaboration.