Senior Machine Learning Engineer

TensorWave; Las Vegas (NV); On-site; USD 120,000 - 150,000; Full time

Benefits offered by this job

Competitive Salary

Stock Options

100% paid Medical, Dental, and Vision insurance

Flexible PTO

Paid Holidays

401(k)

Parental Leave

Flexible Spending Account

Short Term Disability Insurance

Life and Voluntary Supplemental Insurance

Mental Health Benefits

Job summary

A cutting-edge technology company is seeking a Senior Machine Learning Engineer to build and operate systems that power large-scale machine learning training. This role includes designing ML infrastructure, optimizing performance, and enhancing developer experiences. Candidates should have a Bachelor’s degree in Computer Science and expertise in SLURM, Kubernetes, and GPU workloads. The company offers competitive salary, stock options, full medical benefits, flexible PTO, and a mission-driven culture promoting inclusion.

Qualifications

• 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.

Responsibilities

• Design and improve ML infrastructure systems supporting distributed workloads.
• Build workload execution and orchestration patterns across GPU environments.
• Troubleshoot performance and scalability issues.
• Partner with teams to improve developer experience.

Skills

Production ML systems

Performance optimization

Cluster operations

Workload orchestration

Automation tooling

Education

Bachelor of Science in Computer Science or related field

Tools

SLURM

Kubernetes

Python

Go

Job description

About the role

Our mission at Tensorwave Cloud is to build seamless, secure, reliable, and resilient AI infrastructure at scale, eliminating barriers and challenging the status quo to empower builders and support AI innovation.

We are seeking a Senior Machine Learning Engineer to build and operate the core systems that power large-scale ML training and inference across TensorWave’s GPU platform.

This role spans workload orchestration, cluster operations, performance optimization, and developer enablement for production ML workloads.

Responsibilities

• 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

Required Experience

• 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 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

What We Bring

• Mission driven company
• Competitive Salary
• Stock Options
• 100% paid Medical, Dental, and Vision insurance
• Flexible PTO
• Paid Holidays
• 401(k)
• Parental Leave
• Flexible Spending Account
• Short Term Disability Insurance
• Life and Voluntary Supplemental Insurance
• Mental Health Benefits through Spring Health

We’re looking for resilient, adaptable people to join our team, people who believe in the mission and think at massive scale. The solutions that worked on a handful of devices will not work at Exascale. Be prepared to be pushed daily, to learn a lot, and literally build the future.

Tensorwave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, national origin, or veteran status.