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Cuda Kernel Engineer Jobs in Nevada (NOW HIRING)

Senior Solutions Engineer

Las Vegas, NV · On-site

$52.75 - $68/hr

If you're an engineer who loves the detective work of kernel-level debugging and high-performance ... Proficient in orchestrating GPU workloads and diagnosing training job failures using ROCm or CUDA.

Senior Solutions Engineer

Las Vegas, NV · On-site +1

$52.75 - $68/hr

If you're an engineer who loves the detective work of kernel-level debugging and high-performance ... Proficient in orchestrating GPU workloads and diagnosing training job failures using ROCm or CUDA.

Kernel Development : Design and maintain high-performance GPU kernels in Triton or CUDA for state-of-the-art ML workloads. * Data Pipeline Engineering : Optimize robust data loading pipelines that ...

Cuda Kernel Engineer information

What are common challenges faced by CUDA Kernel Engineers when optimizing GPU code for performance?

Cuda Kernel Engineers often encounter challenges such as managing memory hierarchy efficiently, minimizing data transfer between host and device, and avoiding thread divergence. Ensuring optimal occupancy and maximizing parallelism while preventing bottlenecks like bank conflicts or uncoalesced memory access are also key concerns. Collaborating closely with software architects and data scientists is common, as solutions frequently require balancing algorithmic accuracy with hardware limitations. Addressing these challenges requires continuous profiling, testing, and iterative optimization.

What is a CUDA Kernel Engineer?

Cuda Kernel Engineers are specialized software developers who design, implement, and optimize parallel computing algorithms using NVIDIA's CUDA platform. They write 'kernels,' which are functions that run on Graphics Processing Units (GPUs) to accelerate computational tasks in areas such as machine learning, scientific simulations, and graphics rendering. These engineers need strong skills in C/C++ programming, GPU architecture, and performance optimization techniques. Their work is crucial for applications that require high-speed data processing and efficient resource utilization.

What skills and qualifications are needed to be a CUDA Kernel Engineer?

To thrive as a CUDA Kernel Engineer, you need strong proficiency in C/C++ programming, parallel computing concepts, and a solid foundation in GPU architectures, typically supported by a degree in computer science or a related field. Expertise in NVIDIA CUDA toolkits, GPU profiling tools like Nsight, and familiarity with version control systems are essential. Analytical thinking, problem-solving abilities, and effective collaboration skills help engineers optimize code and work well within development teams. These skills and qualities are crucial for delivering high-performance, scalable GPU solutions in computationally intensive applications.
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Senior Solutions Engineer

TensorWave

Las Vegas, NV • On-site

$52.75 - $68/hr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 13 days ago


Job description

About TensorWave

Our mission is simple: deliver seamless, secure, reliable, and resilient AI compute at scale. We've built a versatile cloud platform that eliminates infrastructure barriers, empowering builders to focus on innovation instead of fighting their stack. Because breakthrough AI should move at the speed of ideas, not infrastructure.

About the Role

We're looking for a Senior Solutions Engineer to serve as the elite escalation point between our Global Operations Center (GOC) and our Core Engineering teams. You are the technical backstop for our most sophisticated customers teams training large models who cannot afford a single hour of downtime.

You'll own the problems that go beyond runbooks, sitting at the intersection of customer success and engineering: resolving the hardest technical blockers and translating those findings into a more resilient product. If you're an engineer who loves the detective work of kernel-level debugging and high-performance networking, and who also thrives in the high stakes environment of customer-facing resolution, this is your role.

What You’ll Do

  • Resolve Complex Escalations: Act as the final authority on issues exceeding GOC scope, utilizing code-level debugging and architectural investigation.

  • Direct Customer Engagement: Partner with customer technical leads to diagnose production issues, ensuring transparency and rapid resolution through active collaboration.

  • Iterative Problem Solving: Develop diagnostic scripts and workarounds to maintain customer operations while long-term patches are in development.

  • Drive Root Cause Analysis: Own end-to-end P1 resolution, partnering with TAMs to deliver clear, actionable post-incident analysis.

  • Bridge to Engineering: Convert recurring customer pain points into evidence-based feature requests, influencing product roadmap to resolve systemic failures.

  • Build Scalable Knowledge: Document non-obvious platform behaviors and refine GOC runbooks, ensuring institutional knowledge grows with every incident.

Who You Are

Required Qualifications

  • 5–9 years in Infrastructure Engineering, Platform Engineering, or SRE, with a specific focus on high-performance computing or large-scale AI stacks. Proven track record of managing complex production environments where system reliability is mission-critical.

  • Kubernetes Expert: Deep experience in cluster administration and scheduler internals; comfortable reading/modifying controller code.

  • AI/GPU Infrastructure Specialist: Proficient in orchestrating GPU workloads and diagnosing training job failures using ROCm or CUDA.

  • Network Pathologist: Skilled in RDMA/RoCEv2, SRIOV, and BGP; capable of interpreting switch telemetry to identify silent packet drops.

  • Linux Power User: Expert in kernel networking, hugepages, and cgroups; able to debug at the OS layer when applications are silent.

  • Builder Mindset: Proficient in Python and Ansible; capable of writing custom diagnostic tools to automate remediation.

  • Executive Communicator: Strong technical rigor when presenting findings to VPs of Engineering, maintaining trust while delivering difficult updates.

Preferred Qualifications

  • Prior experience in a customer-facing engineering role (e.g., Solutions Engineering, Technical Support Engineering).

  • Experience in high-uptime environments where 24/7/365 availability is required.

What We Offer

  • Stock Options

  • 100% paid Medical, Dental, and Vision insurance for Employees

  • Company Health Savings Account Contributions

  • 100% paid Short Term and Long Term Disability Insurance for Employees

  • Life and Voluntary Supplemental Insurance Options

  • Other Insurance Options, such as Pet & Legal Insurance

  • Various Supplementary Health Benefits, such as discounted Virtual Healthcare Appointments and Serious Illness Support

  • Flexible Spending Account

  • 401(k)

  • Employee Assistance Program

  • Flexible PTO

  • Paid Holidays

  • Parental Leave

  • Other In-Office Perks

Equal Employment Opportunity

TensorWave is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of any protected status under applicable law.

Reasonable Accommodations

TensorWave provides reasonable accommodations in accordance with applicable laws. If you require accommodation during the hiring process, please contact accomodations@tensorwave.com.

Employment Eligibility

All offers of employment are contingent upon verification of identity and authorization to work in the United States, as required by law.

Background Checks

Where permitted by law, employment may be contingent upon the successful completion of a job-related background check.

Data Privacy Notice

By submitting an application, you acknowledge that TensorWave may collect, use, and retain your personal information for recruiting and employment-related purposes in accordance with applicable data privacy laws.