Technical Writer

📋 Description

• • Own the complete documentation lifecycle for Ray and Anyscale, from strategy to publication. You will create the north-star vision for how developers discover, learn, and succeed with distributed ML, then translate that vision into a prioritized roadmap that balances open-source needs with enterprise requirements.
• • Immerse yourself in the Ray community—GitHub issues, Slack threads, user forums, customer calls—to surface the exact moments where unclear docs stall adoption. Convert these pain points into crisp, searchable, and example-rich guides, tutorials, API references, and architecture diagrams that cut ramp-up time from days to minutes.
• • Partner daily with product managers, ML engineers, and DevOps teams to co-design feature launch assets. You will write release notes, usage examples, and migration guides that ship the same day the code merges, ensuring every new capability is instantly usable.
• • Drive cross-functional launches that blend documentation with marketing. You will script and co-host webinars, author technical blog posts, and craft conference talks that showcase real-world Ray deployments at companies like OpenAI, Uber, and Spotify—turning technical depth into compelling stories that accelerate adoption.
• • Unify the voice and structure of all ML-related docs—training, tuning, serving, reinforcement learning, and more—so that a data scientist exploring hyper-parameter search finds the same clarity as a platform engineer scaling inference to 10,000 GPUs.
• • Champion accessibility and inclusivity in technical communication. You will ensure examples work on laptops, cloud VMs, and managed Anyscale clusters alike, and that language welcomes newcomers without dumbing down content for experts.
• • Establish metrics that matter: time-to-first-success, doc-driven support ticket reduction, and community-contributed PRs. Iterate relentlessly using analytics, user interviews, and A/B tests to raise the bar on developer delight.
• • Mentor junior writers and engineers on documentation best practices, creating templates, style guides, and automated linting that scale quality across the organization.
• • Stay ahead of the rapidly evolving ML landscape—transformers, LLMs, Ray 2.x features—translating cutting-edge research into practical guidance before the community even asks for it.
• • Represent Anyscale at open-source summits and Ray meetups, gathering feedback in real time and bringing it back to continuously refine the docs and the product itself.