*Note: This position requires presence in our San Francisco or San Jose office location 4 days per week; Lambda's designated work from home day is currently Tuesday.
Every GPU cloud provider claims to offer faster, cheaper, and more reliable solutions. ML engineers and decision-makers must sift through these promises to form a trustworthy opinion. Lambda fills the gap between claims and real outcomes.
You own the entire process, from strategy to production. Your audience may be a researcher testing a training run or an enterprise buyer building a procurement case, but you control the message. You set the standards, build the system, and define the quality.
What You'll Do- Own the strategy and the roadmap. Map content to the full buyer journey, from awareness and education through evaluation and retention, against Lambda's growth, product, and brand goals.
- Set and maintain the quality bar. Establish rigorous quality standards that empower the team to execute with excellence independently.
- Run the production system. Intake, prioritization, drafting, review, and launch, at the cadence of product and model releases.
- Shape how AI gets used in content production. Build the workflows and standards that let AI speed up the work without lowering the bar.
- Own discovery. SEO and generative engine optimization (GEO) are how most people find us. Keyword research, content gap analysis, and on-page work are inputs to strategy, not a cleanup pass at the end.
- Build the executive voice. Turn Lambda's narrative into thought leadership that holds up in front of ML engineers and data center operators.
- Partner on launches. Work with technical product marketing and growth so every major launch and campaign is supported by a well-timed, end-to-end content program.
- Own measurement. Traffic, engagement, pipeline influence, and content-assisted conversion, fed back into what the team makes next.
- Build the team. Hire, develop, and shape the content org as it grows.
You- You have taste. You can't walk past a vague sentence or a case study that says nothing. You know the difference between content that's technically correct and content that's actually worth reading, and you can teach that difference to someone else.
- You're deeply curious about AI. You follow model releases, read top papers, and understand why memory bandwidth matters to an ML engineer. You can tell when a technical claim is load-bearing and when it's decoration.
- You have a point of view on AI-assisted content. You've produced work with these tools yourself, you know what to trust them with, and you have opinions about where they break down.
- You've led a content function, not just a content calendar. You've managed and grown people, and you can point to content you shipped and results you can attribute to it.
- You think in systems. You design content architectures, not individual pieces. You understand how a benchmark post, a technical guide, and a case study work together.
- You balance strategy and execution. You can build a 12-month roadmap and then sit with a writer to get one hard piece over the line. Neither mode intimidates you.
- You excel at cross-functional leadership. You work with technical product marketers, researchers, engineers, designers, and web marketers, and you synthesize all of it into one coherent editorial vision.
- You're rigorous about measurement. You define what working means, instrument for it, and act on what you find.
Nice to Have- Experience writing or editing for ML practitioners, whether at an infrastructure company, a research lab, or a developer tools start-up.
- Experience building AI-assisted production workflows for content or other creative work.
- A track record building organic and generative search visibility in the AI space.
Salary Range InformationThe annual salary range for this position has been set based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.
