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Gpu Performance Engineer Jobs in Davis, CA (NOW HIRING)

Ddn

Senior/Staff AI Engineer

Sacramento, CA · On-site

$140 - $200/hr

Improve performance across GPU and CPU pathways * Work on KV cache, memory, storage, and throughput ... Solve engineering problems at the intersection of AI, high-performance systems, and distributed ...

All JobsGpu Performance Engineer JobsGpu Performance Engineer Jobs in Davis, CA

Gpu Performance Engineer information

See Davis, CA salary details

$11

$64

$106

How much do gpu performance engineer jobs pay per hour?

As of Aug 16, 2026, the average hourly pay for gpu performance engineer in Davis, CA is $64.97, according to ZipRecruiter salary data. Most workers in this role earn between $53.27 and $73.51 per hour, depending on experience, location, and employer.

What are some common challenges faced by a GPU performance engineer when optimizing graphics workloads?

GPU Performance Engineers often encounter challenges such as identifying performance bottlenecks within complex graphics pipelines, balancing resource utilization, and achieving optimal frame rates across diverse hardware configurations. They must use specialized profiling tools and collaborate closely with developers, driver engineers, and QA teams to address issues like memory bandwidth limitations or shader inefficiencies. Staying updated with rapidly evolving GPU architectures and optimizing for both current and next-generation hardware are also key aspects of the role.

What is a GPU performance engineer?

A GPU Performance Engineer is a specialist who analyzes, optimizes, and improves the performance of graphics processing units (GPUs). They work on identifying bottlenecks, optimizing code, and ensuring that GPU hardware and software deliver maximum efficiency and speed. Their role may involve working with drivers, firmware, and applications to enhance graphics and compute workloads. This job is essential in industries like gaming, AI, and high-performance computing where GPU efficiency directly impacts user experience and system performance.

What are the key skills and qualifications needed to thrive as a GPU performance engineer, and why are they important?

To thrive as a GPU Performance Engineer, you need a strong background in computer architecture, programming (C/C++), and a degree in computer science, electrical engineering, or a related field. Proficiency with GPU profiling tools (e.g., NVIDIA Nsight, AMD Radeon GPU Profiler), performance analysis frameworks, and parallel computing libraries like CUDA or OpenCL is typically required. Analytical thinking, problem-solving abilities, and effective communication are crucial soft skills for collaborating with developers and debugging performance bottlenecks. These skills and qualities are essential for optimizing GPU performance, ensuring efficient software-hardware interaction, and delivering high-quality graphics or compute solutions.

What is the difference between Gpu Performance Engineer vs Gpu Hardware Engineer?

AspectGpu Performance EngineerGpu Hardware Engineer
Primary FocusOptimizing GPU performance, benchmarking, and tuning softwareDesigning, developing, and testing GPU hardware components
Required SkillsProgramming, performance analysis, GPU architecture knowledgeHardware design, circuit analysis, FPGA/ASIC experience
Work EnvironmentSoftware development teams, labs for testing performanceHardware labs, manufacturing facilities, R&D centers
Common CertificationsNone specific, often requires computer engineering or related degreesElectrical engineering, VLSI design certifications

The Gpu Performance Engineer primarily focuses on optimizing and testing GPU software performance, while the Gpu Hardware Engineer designs and develops the physical GPU components. Both roles require a strong background in computer engineering, but differ in their core responsibilities and work environments.

What job categories do people searching Gpu Performance Engineer jobs in Davis, CA look for?

The top searched job categories for Gpu Performance Engineer jobs in Davis, CA are:

What cities near Davis, CA are hiring for Gpu Performance Engineer jobs?

Cities near Davis, CA with the most Gpu Performance Engineer job openings:

Gpu Performance Engineer jobs near you

Senior Software Engineering Manager - KV Cache Platform

Ddn

Sacramento, CA • On-site

$190 - $260/hr

Other

Posted 11 days ago

Job description

DDN is seeking a Senior Software Engineering Manager to lead the engineering organization responsible for our KV Cache Platform—a distributed memory and storage platform that accelerates large-scale LLM inference across GPU clusters.

In this role, you will lead geographically distributed engineering teams responsible for building highly scalable, low-latency distributed systems that power AI inference. You will define the technical vision and execution strategy for the platform while partnering closely with Product Management, Sales, Customer Engineering, NVIDIA, and executive leadership to deliver innovative AI infrastructure that meets customer needs and supports DDN's long-term product strategy.

This is a highly visible leadership role with responsibility for engineering execution, customer success, roadmap delivery, and building a world-class engineering organization.

Responsibilities

  • Lead, mentor, and grow a geographically distributed team of software engineers and technical leaders, fostering a culture of technical excellence, innovation, ownership, and collaboration.

  • Define and execute the technical strategy and roadmap for the KV Cache Platform, ensuring scalability, reliability, security, and operational excellence.

  • Drive the architecture, development, and delivery of distributed systems supporting AI inference, GPU memory optimization, distributed caching, RDMA networking, GPUDirect Storage, NVIDIA BlueField DPUs, and emerging AI infrastructure technologies.

  • Partner closely with Product Management, Sales, Customer Engineering, NVIDIA, and strategic technology partners to prioritize customer requirements, drive proof‑of‑concepts (POCs), influence product direction, and successfully deliver customer deployments.

  • Own day‑to‑day engineering execution, including feature development, release planning, bug triage, production issues, customer escalations, and cross‑functional execution to ensure timely, high‑quality software delivery.

  • Establish engineering best practices for software quality, observability, automation, performance, testing, and production readiness.

  • Collaborate across engineering, infrastructure, and hardware teams to deliver scalable, production‑ready AI infrastructure while developing future engineering leaders and driving continuous improvement.

Qualifications Required

  • 15+ years of experience building distributed systems, cloud infrastructure, storage platforms, or AI infrastructure software.

  • 7+ years leading high‑performing software engineering organizations, including geographically distributed teams.

  • Proven experience delivering large‑scale distributed infrastructure products from architecture through production deployment.

  • Strong background in distributed systems, Linux, networking, performance engineering, and cloud‑native architectures.

  • Hands‑on programming experience with Go and Python; experience with C/C++ is a plus.

  • Demonstrated ability to lead cross‑functional initiatives and influence technical direction across multiple organizations.

  • Experience building AI infrastructure, LLM serving platforms, distributed caching systems, or high‑performance storage solutions.

  • Experience with technologies such as NVIDIA Dynamo, TensorRT‑LLM, Triton, RDMA, GPUDirect Storage, BlueField DPUs, Kubernetes, or related AI infrastructure.

  • Background in HPC, distributed storage, networking, or enterprise infrastructure software.

  • Experience working directly with strategic customers, technology partners, OEMs, or hyperscalers to deliver enterprise AI solutions.

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