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Gpu Performance Engineer Jobs in Massachusetts (NOW HIRING)

Zoox

Software Engineer - C++ GPU Performance

Boston, MA · On-site

$168K - $239K/yr

As a GPU performance software engineer within the Software Performance team, you will instrument, monitor, analyze and optimize GPU-based algorithms that are performance-critical for our solution.

Zoox

Software Engineer - C++ GPU Performance

Boston, MA · On-site

$168K - $239K/yr

As a GPU performance software engineer within the Software Performance team, you will instrument, monitor, analyze and optimize GPU-based algorithms that are performance-critical for our solution.

Zoox

Software Engineer - C++ GPU Performance

Boston, MA

$168K - $239K/yr

As a GPU performance software engineer within the Software Performance team, you will instrument, monitor, analyze and optimize GPU-based algorithms that are performance-critical for our solution.

Qualcomm

GPU Software Engineer

Boxborough, MA · On-site

$98K - $148K/yr

Qualcomm Graphics Software Engineers architect, design, implement, verify, and optimize the structure and performance of GPU hardware, drivers, features, applications, and tools. Qualcomm Engineers ...

Nvidia

Senior GPU Architect

Westford, MA

$134K - $182K/yr

... graphics performance, parallel programming models or parallel computing performance. You would ... GPU or CPU architecture (or other equivalent experience). * Strong programming ability inC, C ...

Analysis Group, Inc.

AI HPC Infrastructure Engineer

Boston, MA · Hybrid

$117K - $153K/yr

The AI HPC Infrastructure Engineer owns the operation, performance, and growth of a hybrid high-performance computing (HPC) and AI/GPU infrastructure environment. The engineer maintains the Linux ...

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Analysis Group, Inc.

AI HPC Infrastructure Engineer

Boston, MA · On-site

$117K - $153K/yr

The AI HPC Infrastructure Engineer owns the operation, performance, and growth of a hybrid high-performance computing (HPC) and AI/GPU infrastructure environment. The engineer maintains the Linux ...

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Gpu Performance Engineer information

What are some common challenges faced by GPU Performance Engineers 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 are popular job titles related to Gpu Performance Engineer jobs in Massachusetts? For Gpu Performance Engineer jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Gpu Performance Engineer jobs in Massachusetts look for? The top searched job categories for Gpu Performance Engineer jobs in Massachusetts are:
What cities in Massachusetts are hiring for Gpu Performance Engineer jobs? Cities in Massachusetts with the most Gpu Performance Engineer job openings:
Gpu Performance Engineer jobs near you
Infographic showing various Gpu Performance Engineer job openings in Massachusetts as of July 2026, with employment types broken down into 91% Full Time, 5% Part Time, and 4% Contract. Highlights an 89% Physical, 4% Hybrid, and 7% Remote job distribution.

Software Engineer - C++ GPU Performance

Zoox

Boston, MA • On-site

$168K - $239K/yr

Full-time

Medical, Life, PTO

Re-posted 17 days ago

Job description

Zoox is building the world's most advanced self-driving hardware and software solution. The efficiency demands of such a system require an expert fine tuning of both the compute hardware architecture as well as the algorithms and middleware that runs on it to achieve maximum throughput at the most optimal power levels.
The Software Performance team's mission is to analyze, optimize and provide guidance to the software and hardware teams in order to meet the required specifications.
As a GPU performance software engineer within the Software Performance team, you will instrument, monitor, analyze and optimize GPU-based algorithms that are performance-critical for our solution. The scope for GPU usage ranges from traditional computer vision and deep learning architectures to complex geometric reasoning and multi-agent decision making. Your work will strongly influence design decisions of future compute platforms & resource allocation.
In this role, you will:
  • Build real-time instrumentation for performance monitoring (CPU, GPU, latency, memory) and develop offline benchmarking frameworks, tools, and scripts to evaluate & analyze performance at scale in CI/vehicle, and establish budgets for next-gen architectures.
  • Analyze performance metrics to identify GPU hotspots and root causes, and propose and co-implement actionable solutions with component teams.
  • Support teams on bringing serial algorithms to the GPU to maximize compute utilization and improve overall latency.
  • Work as part of the Core team to design a middleware framework that promotes by default efficient and performant code development by maximizing CPU and GPU.

Qualifications
  • BS in computer science or related field and 3+ years of experience.
  • Strong knowledge of CUDA as applied to recent GPU microarchitectures (e.g., Ampere, Blackwell) and experience debugging/optimizing GPU kernels using tools like Nsight.
  • Strong knowledge of C++ and experience in large code bases, comfortable in Linux development environments.
  • Experience in development, debugging, and profiling of complex multiprocess systems (e.g., robotic systems, game engines).

Bonus Qualifications
  • Experience with GPU kernel development in a real-time environment, including PTX-level programming, CPU SIMD instructions (e.g., AVX intrinsics), and custom CUDA layers with frameworks like TensorRT & XLA.
  • Hands-on work with ML model optimization (post-training quantization, layer pruning, etc) or hand-tuning GPU kernels (in OpenGL, CUDA, RocM or similar).
  • Proficiency with SQL, DataBricks, Looker, or other business intelligence tools.

$168,000 - $239,000 a year
Base Salary Range
There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.
Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.
About Zoox
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We're looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
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Accommodations
If you need an accommodation to participate in the application or interview process please reach out to [email protected] or your assigned recruiter.
A Final Note:
You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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