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Alembic Limited

Technical Writer - AI Science Job at Alembic Limited in San Francisco

Alembic Limited, San Francisco, CA, US, 94199

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About Alembic

Alembic is where top engineers are solving marketing's hardest problem: proving what actually works. If you're looking for frontier technical challenges at an applied science company, this is the place.

At Alembic, we're not just building software-we're decoding the chaos of modern marketing. Join Alembic to build trusted systems that Fortune 100 companies use to make multimillion-dollar decisions. We're backed by leading tech luminaries including WndrCo (founded by DreamWorks founder Jeffrey Katzenberg), Jensen Huang, Joe Montana, and many more.

About the Role

We're looking for a Technical Writer focused on R&D and AI Science to document and communicate our AI/ML research, algorithms, and data products. You'll translate complex technical concepts into clear, accurate documentation that enables knowledge sharing across our R&D team and accelerates innovation.

This is a unique opportunity to work at the intersection of technical writing and cutting-edge AI/ML research-documenting breakthrough algorithms, Python SDKs, and the science behind marketing causation.

What You'll Do
  • Create comprehensive documentation for internal AI/ML systems, algorithms, and research methodologies within first 3 months
  • Document Python SDKs, APIs, and data tools to accelerate developer onboarding and reduce support requests by 40%
  • Translate complex research findings into technical specifications, white papers, and internal knowledge base articles
  • Build and maintain a scalable documentation system that grows with R&D team expansion
  • Collaborate with data scientists and engineers to capture and disseminate best practices and technical insights
  • Produce technical blog posts and thought leadership content that showcases Alembic's scientific innovations
What Will Help You Succeed

Technical Writing & Communication
  • 3-5+ years technical writing experience with focus on software, data, or AI/ML products
  • Strong technical aptitude - ability to quickly learn and explain complex algorithms, data structures, and AI/ML concepts
  • Excellent communication skills - can translate complex technical concepts for different technical audiences
  • Experience documenting APIs and SDKs using modern documentation tools (Swagger/OpenAPI, Sphinx, MkDocs)
  • Experience with documentation-as-code workflows (Git, Markdown, version control)
Technical Skills
  • Python proficiency - comfortable reading Python code and documenting APIs, libraries, and data pipelines
  • Understanding of data science workflows - familiarity with concepts like ETL/ELT, data modeling, ML pipelines
  • Self-directed learner - comfortable diving into codebases, asking questions, and figuring things out independently
Advanced Experience
  • Background in computer science, data science, or related technical field
  • Experience working embedded with engineering or research teams
  • Familiarity with ML/AI concepts (model training, inference, feature engineering, causation vs correlation)
  • Experience creating technical diagrams and visualizations (system architecture, data flows)
  • Understanding of statistical concepts and causal inference methodologies
  • Experience with Jupyter notebooks and literate programming approaches
  • Prior work documenting data platforms, analytics tools, or ML infrastructure
Nice to Haves
  • Contributions to open-source technical documentation
  • Experience writing research papers, technical blog posts, or white papers
  • Background in mathematics, statistics, or quantitative fields
  • Familiarity with GPU computing or high-performance computing documentation
  • Experience with tools like Notion, Confluence, ReadTheDocs, or Docusaurus
  • Interest in marketing analytics, causal inference, or econometrics
Why You Might Be Excited About Alembic
  • Hard problems with real impact: You'll tackle the hardest challenges in marketing analytics while building systems that influence multimillion-dollar decisions at Fortune 100 companies
  • Technical autonomy: You want ownership over technical decisions and the freedom to solve complex problems your way
  • Cutting-edge technology: Work with advanced AI/ML algorithms, composite AI solutions, private NVIDIA DGX clusters, and the latest in data processing at scale
  • Elite team: Join top engineers who thrive on challenging problems and high-impact work
  • Startup upside: Early-stage equity opportunity with experienced leadership and proven product-market fit
Why You Might Not Be Excited
  • If you only want to tell people what to build instead of building and coding alongside them, we're not the environment for you
  • You prefer company practices with 100% built-out process for every detail
  • You prefer static over dynamic. Projects, priorities, and roles will adapt to your skill set and goals. Though we have real paying customers and a playbook for growth, we proudly remain an early-stage startup