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Mxv is hiring: Technical Writer - AI Science in San Francisco
Mxv is hiring: Technical Writer - AI Science in San FranciscoMediabistro • San Francisco, CA, United States
Mxv is hiring : Technical Writer - AI Science in San Francisco

Mxv is hiring : Technical Writer - AI Science in San Francisco

Mediabistro • San Francisco, CA, United States
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  • serp_jobs.job_card.full_time
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Location

San Francisco HQ

Employment Type

Full time

Location Type

On-site

Department

R&D

AI Science

Compensation

  • Senior
  • $162K – $192K
  • Offers Equity

Our Compensation Philosophy :

  • Market-based : Our formula ensures new hires earn at or above real-time benchmarks.
  • Ownership : Our generous equity program ensures new hires are owners, not just employees.
  • Transparent : We openly discuss salary expectations to avoid surprises later in the process.
  • Data-driven : We use objective data to remove bias and ensure consistency in compensation decisions.
  • 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

    Compensation Range : $162K - $192K

    #J-18808-Ljbffr

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    Technical Writer • San Francisco, CA, United States

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