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Kernel Trading Technologies Jobs in California (NOW HIRING)

E2B

Platform Engineer

San Francisco, CA · On-site

$250K - $350K/yr

Our team includes original authors of Firecracker, the AWS microVM technology powering Lambda ... Building an observability stack starting at the kernel level of virtual machines We're looking for ...

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Kernel Trading Technologies information

What is a Kernel Trading Technologies?

A Kernel Trading Technologies job typically involves developing and maintaining high-performance trading systems, specializing in low-latency and algorithmic trading solutions. Professionals in this field work on optimizing trading infrastructure, implementing market connectivity solutions, and enhancing risk management tools. They often collaborate with traders, quantitative researchers, and software engineers to improve execution speed and reliability. Strong programming skills, particularly in C++ or Python, and a deep understanding of financial markets are essential.

What are the key skills and qualifications needed to thrive in the Kernel Trading Technologies position, and why are they important?

To excel in Kernel Trading Technologies, candidates need a strong background in computer science, quantitative analysis, and algorithmic trading, often supported by a relevant degree. Familiarity with C/C++ or Python, low-latency trading systems, and experience with exchanges and financial protocols are highly valued. Analytical thinking, teamwork, and adaptability help professionals navigate complex trading environments and collaborate effectively. These skills ensure optimal system performance and successful execution in highly competitive financial markets.

What are common challenges faced by professionals working in Kernel Trading Technologies roles?

Professionals in Kernel Trading Technologies roles often encounter the challenge of balancing speed, reliability, and security when optimizing trading systems under strict latency requirements. They must troubleshoot and resolve issues rapidly in a high-pressure environment, as even minor delays can impact trading results. Close collaboration with traders, software engineers, and infrastructure teams is essential for effective deployment and continuous improvement. Successfully navigating these challenges sharpens both technical and teamwork skills, making the role both demanding and highly rewarding.

What are the most commonly searched types of Kernel Trading Technologies jobs in California?

The most popular types of Kernel Trading Technologies jobs in California are:

What are popular job titles related to Kernel Trading Technologies jobs in California?

For Kernel Trading Technologies jobs in California, the most frequently searched job titles are:

What job categories do people searching Kernel Trading Technologies jobs in California look for?

The top searched job categories for Kernel Trading Technologies jobs in California are:

Kernel Trading Technologies jobs near you
Infographic showing various Kernel Trading Technologies job openings in California as of August 2026, with employment types broken down into 86% Full Time, 7% Part Time, 2% Temporary, 4% Contract, and 1% Nights. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution.

Software Engineer - GPU Kernel

FriendliAI Corp

San Francisco, CA • On-site

Full-time

Medical

Re-posted 24 days ago

Job description

About the job
FriendliAI is looking for a GPU Kernel Engineer to design, build, and optimize the low-level compute kernels that power our large-scale, GPU-accelerated AI inference platform. You will be delivering world-class inference speed across NVIDIA and AMD GPUs. With our recent $20M funding, we are scaling our team to meet market demand.
This is a deeply technical, high-impact role where you will write GPU code, implement advanced optimizations. As part of our engine team, you will contribute directly to the company's proprietary inference engine which supports over 600,000 models on Hugging Face. You will work with the inventors of continuous batching and collaborate with the platform team to deploy your work into production.
Key Responsibilities
  • Design, implement, and optimize high-performance GPU kernels for AI inference (e.g., GEMM, attention, routing)
  • Develop and maintain GPU code in CUDA and C++, including low-level assembly when needed
  • Implement reduced-precision and quantized kernels (FP8/FP4) for low-latency or high-throughput inference
  • Benchmark and ensure cross-vendor performance parity between NVIDIA and AMD hardware
  • Contribute to internal GPU libraries and tune performance of performance-critical components
  • Accelerate multi-modal model pipelines
  • Investigate and integrate next-generation GPU features
Qualifications
  • 3+ years of experience in GPU programming, HPC, or performance-critical systems
  • Bachelor's or Master's degrees in Computer Science, Computer Engineering, Electrical Engineering, or a related field
  • Strong proficiency in CUDA for NVIDIA GPUs or ROCm/HIP for AMD GPUs
  • Deep understanding of GPU architecture: warps, threads, memory hierarchy, synchronization, and latency-throughput trade-offs
  • Proficiency in C++
  • Experience with GPU profiling and performance tuning
  • Strong numerical background with understanding of precision trade-offs and quantization techniques

Preferred Experience
  • Experience optimizing transformer, multi-modal, or Mixture-of-Experts (MoE) architectures at the kernel level
  • Familiarity with the latest GPU libraries and frameworks (CUTLASS, Triton, ...)
  • Inter-GPU communication programming experience
  • Open-source contributions related to GPU performance or ML acceleration
  • Research or conference presentations on GPU optimization, HPC, or numerical computing

Benefits
  • Flexible working hours
  • Daily lunch and dinner provided; unlimited snacks and beverages
  • Supportive and highly collaborative work environment
  • Health check-up support and top-tier equipment/hardware support
  • A front-row seat to the generative AI infrastructure revolution
  • Competitive compensation, startup equity, health insurance, and other benefits.

About FriendliAI
FriendliAI is building the world's best AI inference platform that makes large language and multi-modal models fast, efficient, and deployable at scale. We power high-throughput, low-latency AI workloads for organizations worldwide and integrate directly with Hugging Face, giving developers instant access to over 600,000 open-source models.
We are a small, fast-moving team doing work that matters at one of the most exciting moments in the history of technology. With our world-class inference engine, we are building a platform that the AI industry can actually rely on.

Apply