Software Engineering Intern

TensorWave
Las Vegas, NV
On-siteCareer-pivot friendly

Who this role is best for

Best suited to candidates with experience in cloud infrastructure and AI/ML systems, working in a high-impact engineering team in Las Vegas, Nevada.

Best fit for

  • Candidates with hands-on experience in GPU cluster automation and observability tools
    — “Work on automation, monitoring, and observability for GPU clusters”
  • Students interested in bare-metal AI cloud operations and performance optimization
    — “Learn how bare-metal AI clouds operate at scale—from hardware partitioning to high-speed networking and storage”
  • Individuals who thrive in small, high-impact engineering teams with exposure to production systems
    — “join a small, high-impact engineering team building the systems that power the future of AI compute”

Things to consider

  • The internship is part-time, with work hours limited to Tuesday through Friday
    — “Tuesday - Friday, 8 hours”
  • The role is contingent on employment eligibility verification and work authorization in the US
    — “All offers of employment are contingent upon verification of identity and authorization to work in the United States”

How to stand out

  • Highlight experience with Slurm and Kubernetes-native environments in your resume
    — “Work on automation, monitoring, and observability for GPU clusters (Slurm + Kubernetes-native environments)”
  • Emphasize your ability to debug performance bottlenecks in inference or training pipelines
    — “Participate in debugging performance bottlenecks in high-throughput inference or distributed training pipelines”
  • Showcase your experience with writing clean, well-tested code and participating in code reviews
    — “Write clean, well-tested code and participate in code reviews”
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Work on features for cloud control plane
  • Participate in debugging performance bottlenecks
  • Learn how bare-metal AI clouds operate at scale
Typical background
Student passionate about cloud infrastructure, AI/ML systems, performance optimization

Skills & requirements

Required

Collaboration With Senior EngineersAutomationMonitoringObservabilityDebugging Performance BottlenecksClean, Well-tested Code

Preferred

Kubernetes-native EnvironmentsAmd's Rocm Ecosystem

Stack & domain

Cloud InfrastructureAi/ml SystemsPerformance OptimizationBare-metal AI CloudsHigh-speed NetworkingStorage

About the role

Original posting from TensorWave via Ashby

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 Software Engineering Intern to join our team during an exciting phase of growth. In this role, you'll join a small, high-impact engineering team building the systems that power the future of AI compute. You'll work on real production challenges in a cutting-edge GPU cloud environment, gaining hands-on experience with bare-metal infrastructure, large-scale distributed systems, and AMD's ROCm ecosystem.

This is an excellent opportunity for students passionate about cloud infrastructure, AI/ML systems, performance optimization, and contributing to tools that AI innovators use every day.

What You’ll Do

  • Collaborate with senior engineers on features for our cloud control plane, orchestration layer, user-facing APIs, or internal tooling
  • Work on automation, monitoring, and observability for GPU clusters (Slurm + Kubernetes-native environments)
  • Participate in debugging performance bottlenecks in high-throughput inference or distributed training pipelines
  • Write clean, well-tested code and participate in code reviews
  • Learn how bare-metal AI clouds operate at scale—from hardware partitioning to high-speed networking and storage

Who You Are

Required Qualifications

  • Collaborate with senior engineers on features for our cloud control plane, orchestration layer, user-facing APIs, or internal tooling
  • Work on automation, monitoring, and observability for GPU clusters (Slurm + Kubernetes-native environments)
  • Participate in debugging performance bottlenecks in high-throughput inference or distributed training pipelines
  • Write clean, well-tested code and participate in code reviews
  • Learn how bare-metal AI clouds operate at scale—from hardware partitioning to high-speed networking and storage

Internship Information

  • Paid Internship
  • May - August (12 weeks)
  • Tuesday - Friday, 8 hours

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.

Source: TensorWave careers (Ashby)

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