tensorwave · Remote
Skills: Python
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 oc…
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