ML Engineer

About The Company
TensorWave is building a versatile cloud platform designed to make AI computing seamless, secure, reliable, and resilient at scale. By reducing infrastructure barriers, we help developers and organizations focus on creating new solutions rather than managing complex systems. Our goal is to enable breakthrough AI work to move at the speed of ideas. We value practical engineering, open collaboration, and a strong connection with the developer community as we continue to expand our platform and ecosystem.
About The Role
TensorWave is seeking an ML Engineer, Developer Ecosystem to serve as the engineering partner to our Developer Ecosystem team. This position sits within the ML team and reports to the VP of AI. You will use your hands-on machine learning expertise to help developers build successfully on TensorWave, creating practical tutorials, reference solutions, and workshop materials that demonstrate how to use the platform. You will also evaluate emerging models and frameworks, support developers at events, and share community feedback with internal teams. This is a collaborative, public-facing engineering role for someone who enjoys both building ML systems and helping others understand how to use them.
Qualifications
Candidates should have a bachelor’s degree in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience, and at least three years of experience building machine learning systems in Python. Strong experience with PyTorch and the Hugging Face ecosystem is required, along with hands-on knowledge of large language model inference frameworks such as vLLM or SGLang. You should be comfortable working with Linux, containers, and GPU environments, and able to communicate technical information clearly in writing, conversation, and presentations.
This role is based in the San Francisco Bay Area and requires availability for regular in-person events and occasional travel. Experience with AMD Instinct GPUs and ROCm, or comparable experience with NVIDIA CUDA, is valuable. Additional preferred experience includes model training and fine-tuning, delivering workshops or technical talks, writing developer-focused documentation or tutorials, and contributing to open-source projects.
Responsibilities
Build, maintain, and improve a library of tutorials and reference solutions for AMD Instinct GPUs, with examples covering inference, model serving, and fine-tuning. Evaluate newly released models and frameworks, then develop working examples that help developers understand their capabilities and run them on TensorWave.
Prepare and deliver technical content for workshops and hackathons, and provide hands-on support to participants as they work through practical challenges. Partner with Marketing to propose technical topics, develop content outlines, and review materials for accuracy and usefulness. Share observations from developer events and community discussions to inform priorities across Marketing and ML. Work closely with ML engineering teams, report issues discovered in relevant tools and frameworks, and contribute fixes to upstream projects when appropriate.
Benefits
TensorWave offers stock options and a comprehensive benefits package. The company pays 100% of employee medical, dental, and vision insurance premiums and contributes to a Health Savings Account. Benefits also include company-paid short-term and long-term disability insurance, life and voluntary supplemental insurance options, and additional coverage such as pet and legal insurance. Employees may have access to supplementary health benefits, including discounted virtual healthcare appointments and serious illness support.
Other offerings include a Flexible Spending Account, a 401(k) plan, an Employee Assistance Program, flexible paid time off, paid holidays, parental leave, and in-office perks.
Equal Opportunity
TensorWave is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment. Employment decisions are made without discrimination based on any status protected by applicable law. Reasonable accommodations are available in accordance with applicable laws; candidates who need an accommodation during the hiring process may contact [email protected]. Offers are contingent upon verification of identity and authorization to work in the United States. Where permitted by law, employment may also be contingent upon a job-related background check. By applying, candidates acknowledge that TensorWave may collect, use, and retain personal information for recruiting and employment-related purposes in accordance with applicable data privacy laws.

Skills
Python, Linux, Machine Learning, PyTorch, Documentation

Experience
3+ yrs

Work arrangement
Yes