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Senior Machine Learning Engineer

Las Vegas, Nevada · Remote · Las Vegas, Nevada, United States

Pay
Salary not listed in the saved posting
Work setup
On-site — work setup source
Location type: On-site
From the employer’s posting
Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting
Team
Engineering › Machine Learning — team source
Department: Engineering › Machine Learning
From the employer’s posting
Apply at Tensorwave

What you’ll work on

Full posting

We’re looking for a Senior Machine Learning Engineer to join our team during an exciting phase of growth.

  • Design, operate, and improve ML infrastructure systems supporting distributed training and inference workloads

  • Build reliable, repeatable workload execution and orchestration patterns across shared GPU environments

  • Partner with ML, systems, and platform teams to improve developer experience and operational efficiency

From the employer’s posting
We’re looking for a Senior Machine Learning Engineer to join our team during an exciting phase of growth. In this role, you’ll be responsible for building and operating the core systems that power large-scale ML training and inference across TensorWave’s GPU platform, working closely with cross-functional partners to support business objectives while upholding our standards for excellence, collaboration, and impact.
What You’ll Do Design, operate, and improve ML infrastructure systems supporting distributed training and inference workloads Build reliable, repeatable workload execution and orchestration patterns across shared GPU environments
Design, operate, and improve ML infrastructure systems supporting distributed training and inference workloads Build reliable, repeatable workload execution and orchestration patterns across shared GPU environments Troubleshoot performance, reliability, and scalability issues across the ML stack
Troubleshoot performance, reliability, and scalability issues across the ML stack Partner with ML, systems, and platform teams to improve developer experience and operational efficiency Who You Are

What you’ll bring

All qualifications

Core experience

  • Bachelor of Science in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience
  • Ability to build automation and tooling - Python, Go, etc.
  • Expertise supporting production ML systems using SLURM and Kubernetes
  • Strong understanding of GPU-accelerated workloads and distributed systems concepts

Preferred experience

  • Experience working across schedulers, orchestration platforms, or cluster managers
  • Familiarity with large-scale GPU environments or HPC-style systems
  • Experience improving infrastructure reliability, utilization, or performance at scale
Qualification wording
Bachelor of Science in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience
Ability to build automation and tooling - Python, Go, etc.
Expertise supporting production ML systems using SLURM and Kubernetes
Strong understanding of GPU-accelerated workloads and distributed systems concepts
Experience working across schedulers, orchestration platforms, or cluster managers
Familiarity with large-scale GPU environments or HPC-style systems
Experience improving infrastructure reliability, utilization, or performance at scale

Tools in this posting

  • Go
  • Python
  • Kubernetes
Source — Tool mentions in context
- Solid Linux fundamentals and experience debugging infrastructure-level issues - Ability to build automation and tooling - Python, Go, etc. Preferred Qualifications
- Bachelor of Science in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience - Expertise supporting production ML systems using SLURM and Kubernetes - Strong understanding of GPU-accelerated workloads and distributed systems concepts

Benefits in the posting

Full benefits wording
  • 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

From the employer’s posting.

About Tensorwave

Our mission is simple: deliver seamless, secure, reliable, and resilient AI compute at scale.

In the employer’s words · Read in context

Job description

View original posting ↗

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 Machine Learning Engineer to join our team during an exciting phase of growth. In this role, you’ll be responsible for building and operating the core systems that power large-scale ML training and inference across TensorWave’s GPU platform, working closely with cross-functional partners to support business objectives while upholding our standards for excellence, collaboration, and impact.

 

What You’ll Do

  • Design, operate, and improve ML infrastructure systems supporting distributed training and inference workloads

  • Build reliable, repeatable workload execution and orchestration patterns across shared GPU environments

  • Troubleshoot performance, reliability, and scalability issues across the ML stack

  • Partner with ML, systems, and platform teams to improve developer experience and operational efficiency

 

Who You Are

Required Qualifications

  • Bachelor of Science in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience

  • Expertise supporting production ML systems using SLURM and Kubernetes

  • Strong understanding of GPU-accelerated workloads and distributed systems concepts

  • Solid Linux fundamentals and experience debugging infrastructure-level issues

  • Ability to build automation and tooling - Python, Go, etc.

Preferred Qualifications

  • Experience working across schedulers, orchestration platforms, or cluster managers

  • Familiarity with large-scale GPU environments or HPC-style systems

  • Experience improving infrastructure reliability, utilization, or performance at scale

 

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.

Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.
  • Ask the employer about the salary range before committing time to the process.

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Source & posting history

View original posting ↗

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Pay

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Location & working pattern

Las Vegas, Nevada, United States

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Status in our records
Active
First seen by us
Jun 2, 2026
Recorded sightings
93
Last seen by us
Oct 13, 2026
Employer says posted
Nov 17, 2025

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