ML Engineer, Developer Ecosystem

About the role

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 an ML Engineer, Developer Ecosystem to serve as the engineering counterpart to our Developer Ecosystem team. Working within the ML team and reporting to the VP of AI, you will build the tutorials, reference solutions, and workshop content that help developers succeed on TensorWave, and bring hands-on ML expertise to our developer events and technical content.

What You’ll Do

Build and maintain a library of tutorials and reference solutions for AMD Instinct GPUs, covering inference, serving, and fine-tuning

Evaluate new models and frameworks as they are released and develop working examples on our platform

Deliver technical content for workshops and hackathons, and support participants during events

Partner with the marketing team on technical content, contributing topics, outlines, and technical review

Share insights from events and the developer community to inform marketing and ML priorities

Collaborate with ML engineering teams and contribute issue reports and fixes to upstream projects

Who You Are

Required Qualifications

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

3+ years of experience building ML systems in Python

Strong experience with PyTorch and the Hugging Face ecosystem

Hands-on experience with LLM inference frameworks such as vLLM or SGLang

Proficiency with Linux, containers, and GPU environments

Strong written and verbal communication skills, including presenting to technical audiences

Based in the San Francisco Bay Area, with availability for regular in-person events and occasional travel

Preferred Qualifications

Experience with AMD Instinct GPUs and the ROCm ecosystem, or equivalent experience with NVIDIA CUDA

Experience with model training and fine-tuning

Experience delivering workshops, talks, or technical training

Experience writing technical documentation, tutorials, or blog posts for developer audiences

Open source contributor

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.

Posting text as published by TensorWave.

The evidence behind this listing

Workplace

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Employment type

full time

Location as listed

Remote

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