At Tecton, we solve the complex data problem in production machine learning. Tecton’s feature platform makes it simple to activate data for smarter models and predictions. Tecton abstracts away the complex engineering to speed up innovation.
Tecton’s founders developed the first Feature Store when they created Uber’s Michelangelo ML platform, and we’re now bringing those same capabilities to every organization in the world.
Tecton is funded by Sequoia Capital, Andreessen Horowitz, and Kleiner Perkins, along with strategic investments from Snowflake and Databricks. We have a fast-growing team that’s distributed around the world, with offices in San Francisco and New York City. Our team has years of experience building and operating business-critical machine learning systems at leading tech companies like Uber, Google, Meta, Airbnb, Lyft, and Twitter.
As the Lead Technical Writer, you’ll own the whole Vision, Strategy, & Execution for Tecton’s technical documentation. Every day you’ll get to work at the forefront of ML & AI innovation, making these new powerful tools more accessible to Data Scientists and Engineers everywhere.
We know that high quality technical documentation is essential for the success of a developer-facing product like Tecton. Your documentation leadership will have enormous impact in helping new developers understand & unlock the value of Tecton.
Lead Technical Writer is a lot of responsibility! To succeed in this role, you need to marry a strong vision for high quality documentation, a passion to simplify the complex, and the technical depth needed to understand the Tecton product and users
Responsibilities
- Own the vision & strategy for Tecton’s documentation. Show us what greatness is, and how we’re going to get there.
- Deeply understand our customers’ learning journey with Tecton. Identify and prioritize improvements so that they learn and get to value faster.
- Define and measure the impact of great documentation.
- Enable subject matter experts from across the organization to make high-quality contributions to our docs.
- Directly craft high quality written content for the most important pages and assets.
- 5+ years in Technical Writing, or similar technical roles (e.g. Product Management, Data Science, Engineering)
- 2+ years in Technical Writing for Data Products or Cloud Platforms.
- Mastery of technical writing tools and style: consistent voice, straightforward and lively style, and understanding of the rules of grammar and usage.
- Understanding of information architecture concepts and how to apply them to a constantly changing website.
- In-depth knowledge of the content development lifecycle, including: understanding the information needs of the audience, gathering information, and reviewing feedback.
- Strong project management skills. You strive in a self-directed environment, and now how to engage cross-functional peers to accomplish joint outcomes.
- Proficiency in documentation-as-code workflows.
- Python & SQL familiarity at the level needed to author and test sample Tecton code.
- Experience using AI to produce high quality technical content.
Tecton values diversity and is an equal opportunity employer committed to creating an inclusive environment for all employees and applicants without regard to race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or other applicable legally protected characteristics. If you would like to request any accommodations from the application through to the interview, please contact us at [email protected].
This employer participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.
What We Do
Founded by the team that created the Uber Michelangelo platform, Tecton provides an enterprise-ready feature store to make world-class machine learning accessible to every company.
Machine learning creates new opportunities to generate more value than ever before from data. Companies can now build ML-driven applications to automate decisions at machine speed, deliver magical customer experiences, and re-invent business processes.
But ML models will only ever be as good as the data that is fed to them. Today, it’s incredibly hard to build and manage ML data. Most companies don’t have access to the advanced ML data infrastructure that is used by the internet giants. So ML teams spend the majority of their time building custom features and bespoke data pipelines, and most models never make it to production.
We believe that companies need a new kind of data platform built for the unique requirements of ML. Our goal is to enable ML teams to build great features, serve them to production quickly and reliably, and do it at scale. By getting the data layer for ML right, companies can get better models to production faster to drive real business outcomes.