Technical Writer - AI Science

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