ML Engineer, Developer Ecosystem

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.