---
title: 'Head of Content at Lambda'
canonical: 'https://feeny.ai/job/head-of-content-lambda-san-francisco-15kka32w1qcg'
type: 'job'
last_seen: '2026-09-13'
---

# Head of Content at Lambda

- **Company:** Lambda
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-09-01
- **Last confirmed live:** 2026-09-13
- **Apply:** https://jobs.ashbyhq.com/lambda/374aaca0-3895-4f44-9075-0ecd8a28b703

## Job description

Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. Our customers range from AI researchers to enterprises and hyperscalers. Lambda's mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence. One person, one GPU.

If you'd like to build the world's best AI cloud, join us.

*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 Information The 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.

## About Lambda

- Founded in 2012, with 500+ employees, and growing fast
- Our investors notably include TWG Global, US Innovative Technology Fund (USIT), Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent Cove
- We have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG
- Our values are publicly available: https://lambda.ai/careers
- We offer generous cash & equity compensation
- Health, dental, and vision coverage for you and your dependents
- Wellness and commuter stipends for select roles
- 401k Plan with 2% company match (USA employees)
- Flexible paid time off plan that we all actually use

## Equal Opportunity Employer

Lambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.

## About Lambda

## Company Overview
- **One-liner**: Lambda builds supercomputers and cloud infrastructure for training and deploying large-scale AI models, from single GPUs to gigawatt-scale AI factories.
- **Entity Type**: Private (funding stage not publicly disclosed; founded by ML engineers)
- **Headquarters**: San Francisco, California, USA
- **Founded**: 2012
- **Founders**: Stephen Balaban and Michael Balaban

## Core Business
- Primary industry: AI infrastructure / cloud computing for machine learning.
- Target customers: Frontier AI labs building large foundation models, hyperscalers scaling global AI infrastructure, and enterprises deploying AI in regulated industries (B2B, Enterprise).
- Mission: “Make compute as ubiquitous as electricity and give everyone in America the power of superintelligence” (also “One person, one GPU”).

## Products & Services
- **The Superintelligence Cloud**: A suite of cloud computing offerings specifically built for AI workloads, including:
  - **GPU Instances**: On-demand NVIDIA HGX B200, H100, and GB300 NVL72 instances for prototyping and testing.
  - **Managed Clusters**: Dedicated, single-tenant clusters (e.g., NVIDIA GB300 NVL72, HGX B200/H100) with full management and co-engineering from Lambda’s team.
  - **1-Click Clusters™**: Rapidly deployable clusters for training and inference.
  - **Superclusters**: Large-scale AI factories integrating high-density power, liquid cooling, and high-bandwidth interconnects.
- **AI Infrastructure Hardware**: Modular AI factory designs and NVIDIA-based systems for on-premise or colocation deployment.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed.
- **Key Metric**: Total funding not publicly available; revenue not disclosed.
- **Notable Customers/Partners**: “World’s most advanced AI organizations” (frontier labs, hyperscalers, regulated enterprises). Leadership includes former executives from cloud and networking companies.
- **Growth Signals**: Active hiring across engineering, storage, security, and procurement roles; building AI factories at gigawatt scale; SOC 2 Type II certified; expanding from San Francisco to San Jose, CA.

## Competitive Advantages
- **AI‑First DNA**: 100% of engineering, operations, and support dedicated to AI – founded by ML engineers in 2012.
- **Single‑Tenant Isolation**: Shared‑nothing architecture for security and performance, with hardware‑level isolation.
- **Full‑Stack Expertise**: Co‑engineering from the same team building the infrastructure, enabling deep optimization for large training runs.
- **Hacker Culture**: Rooted in the Noisebridge hackerspace values of do‑ocracy, low ego, and “be excellent to each other.”
- **Performance**: Rack‑scale NVIDIA systems (GB300, B200, H100) with high‑speed interconnects (NVIDIA Quantum‑2 InfiniBand).

## Strategic Focus
- Scaling infrastructure to support the next generation of superintelligence, including gigawatt‑scale AI factories.
- Enabling frontier labs to train trillion‑parameter models and serve billions of tokens in production.
- Expanding compliance and security capabilities for regulated industries.
- Growing the cloud platform (The Superintelligence Cloud) as the primary go‑to‑market offering.

## Why Work Here
- **Culture**: Hacker ethos (Noisebridge roots), low ego, no yelling, no politics, no crypto. Values: build, move fast, care, be excellent to each other.
- **Work Environment**: Fast‑paced, high‑change, outcome‑focused. Emphasis on technical excellence and curiosity. Anonymous feedback encouraged.
- **Interview Process**: Clear, structured steps (recruiter chat → hiring manager → technical assessment → panel interviews → reference/offer). Pedigree is not everything; focus on what you’ve built.
- **Location & Remote**: Offices in San Francisco and San Jose, CA. FAQ page addresses remote/hybrid policy (details not provided in available snippets); some roles appear on‑site.
- **Perks**: Benefits, time off, and other perks are listed on the careers site (specifics not extracted here).

## Sources
1. [lambda.ai/about](https://lambda.ai/about)
2. [lambda.ai/](https://lambda.ai/)
3. [lambda.ai/careers](https://lambda.ai/careers)
4. [lambda.ai/leadership](https://lambda.ai/leadership)

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