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 [email protected].
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.
Skills Required
- 5+ years of experience in cloud infrastructure, HPC, or machine learning roles
- Significant hands-on experience with Slurm in production HPC/ML environments
- Strong knowledge of distributed ML languages and frameworks (Python, PyTorch, etc.)
- Deep understanding of security, compliance, and resilience in containerized workloads
- 3+ years of hands-on Kubernetes experience
- Experience with DAGs using K8s native tools such as Argo Workflows
What We Do
TensorWave is a cutting-edge cloud platform designed specifically for AI workloads. Offering AMD MI300X accelerators and a best-in-class inference engine, TensorWave is a top-choice for training, fine-tuning, and inference. Visit tensorwave.com to learn more. Send us a message to try it for free.
