Senior Machine Learning Engineer

TensorWave Inc.
Las Vegas, NV, United States
21 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours

Tech stack

Build Automation Computer Engineering Software Debugging Linux Distributed Computing Environment Distributed Systems Python (Programming Language) Machine Learning Performance Tuning Kubernetes Information Technology Slurm
+1 more
Machine Learning Operations

Job description

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, 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.

Requirements

  • 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., * 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

Benefits & conditions

  • 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

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