Alembic Technologies is hiring: Technical Writer - AI Science in San Francisco

Overview

Join to apply for the Technical Writer - AI Science role at Alembic Technologies.

Base pay range

$162,000.00/yr - $192,000.00/yr

Alembic is where top engineers are solving marketing's hardest problems. If you're looking for frontier technical challenges at an applied science company, this is the place. We are building trusted systems that Fortune 100 companies use to make multimillion-dollar decisions and are backed by leading tech luminaries.

Role Overview

We are 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 will 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.

Responsibilities

• Create comprehensive documentation for internal AI/ML systems, algorithms, and research methodologies within the 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 the R&D team
• Collaborate with data scientists and engineers to capture and disseminate best practices and technical insights
• Produce technical blog posts and thought leadership content showcasing 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 — ability to 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 (ETL/ELT, data modeling, ML pipelines)
• Self-directed learner — able to dive into codebases and figure things out independently

• Advanced Experience — Background in computer science, data science, or related technical field; experience 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

• Nice to Haves — Contributions to open-source technical documentation; background in mathematics, statistics, or quantitative fields; familiarity with GPU computing or HPC documentation; experience with Notion, Confluence, ReadTheDocs, or Docusaurus; interest in marketing analytics, causal inference, or econometrics

Details

• Seniority level: Mid-Senior level
• Employment type: Full-time
• Job function: Marketing, Public Relations, and Writing/Editing
• Industries: Software Development