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Assistant Cuda Jobs (NOW HIRING)

Strong knowledge of CUDA as applied to recent GPU microarchitectures (e.g., Ampere, Blackwell) and ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Strong knowledge of CUDA as applied to recent GPU microarchitectures (e.g., Ampere, Blackwell) and ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Strong knowledge of CUDA as applied to recent GPU microarchitectures (e.g., Ampere, Blackwell) and ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Strong knowledge of CUDA as applied to recent GPU microarchitectures (e.g., Ampere, Blackwell) and ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Strong knowledge of CUDA as applied to recent GPU microarchitectures (e.g., Ampere, Blackwell) and ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Software Engineer - C++ GPU Performance

Boston, MA · On-site

$152K/yr

Strong knowledge of CUDA as applied to recent GPU microarchitectures (e.g., Ampere, Blackwell) and ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Strong knowledge of CUDA as applied to recent GPU microarchitectures (e.g., Ampere, Blackwell) and ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

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Assistant Cuda information

What are the key skills and qualifications needed to thrive as an Assistant CUDA Developer, and why are they important?

To thrive as an Assistant CUDA Developer, you need strong programming skills in C/C++, a solid understanding of parallel computing concepts, and familiarity with GPU architectures, often backed by a degree in computer science or a related field. Proficiency with CUDA development tools, debugging utilities, and version control systems like Git is typically required. Attention to detail, problem-solving abilities, and effective communication are crucial soft skills for collaborating with teams and optimizing code. These skills ensure efficient development of high-performance applications and successful integration of GPU acceleration into software solutions.

What are Assistant Cuda roles and responsibilities?

An Assistant Cuda typically supports senior CUDA (Compute Unified Device Architecture) developers or teams working with NVIDIA’s parallel computing platform. Their responsibilities include assisting in developing, testing, and optimizing code written for GPUs to accelerate computing tasks, debugging CUDA applications, and maintaining documentation. They may also handle routine tasks such as performance benchmarking, code reviews, and collaborating with other team members to implement efficient GPU solutions. This role is crucial in organizations that rely on high-performance computing, scientific simulations, or AI workloads.

What is the difference between Assistant Cuda vs Assistant Data Analyst?

AspectAssistant CudaAssistant Data Analyst
Required CredentialsTypically a relevant degree in computer science or related fieldOften a degree in data science, statistics, or related field
Work EnvironmentTech companies, software development teams, AI projectsBusiness, finance, marketing, or research departments
Employer & Industry UsageUsed in tech and AI industries for supporting CUDA programming tasksCommon in data-driven industries for data processing and analysis

Assistant Cuda and Assistant Data Analyst roles share some technical background but differ mainly in focus. Assistant Cuda primarily supports GPU programming and AI development, while Assistant Data Analyst focuses on data interpretation and reporting. Both roles require relevant technical skills and are found in industries leveraging data and technology, but their daily tasks and industry applications vary significantly.

What are some common challenges faced by Assistant CUDA developers when optimizing code for GPU performance?

Assistant CUDA developers often encounter challenges such as managing memory efficiently between the host and device, ensuring proper kernel parallelization, and avoiding thread divergence. Balancing occupancy and resource usage can also be tricky, as it requires a deep understanding of how CUDA schedules and executes threads. Collaborating closely with data scientists and other engineers is essential to identify performance bottlenecks and implement effective optimizations.
More about Assistant Cuda jobs
What cities are hiring for Assistant Cuda jobs? Cities with the most Assistant Cuda job openings:
What are the most commonly searched types of Cuda jobs? The most popular types of Cuda jobs are:
What states have the most Assistant Cuda jobs? States with the most job openings for Assistant Cuda jobs include:
Infographic showing various Assistant Cuda job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 95% Full Time, 1% Temporary, and 3% Contract. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution.

Software Engineer - C++ GPU Performance

Zoox

Seattle, WA

$159K/yr

Full-time

Posted 23 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.
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 accommodations@zoox.com 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. 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.