Position: Technical Writer
Working Hours: Monday to Friday 5:00 AM - 2:00 PM Pacific Time
About the role:
The clients company helps candidates practice with real interview questions. Theyre looking for a self-directed Technical Writer/Content Editor to maintain and improve their interview-question library keeping questions accurate fresh well-tagged and genuinely engaging to solve. You dont need to be a deep expert in every domain but you do need enough Python/SQL fluency and product sense to know when something is correct unclear or outdated and to fix it quickly.
Responsibilities:
- Own the question bank. Review edit and publish interview questions and solutions across Data Science Analytics ML/AI and Data Engineering categories.
- Raise quality. Rewrite unclear prompts/solutions standardize difficulty and tags add hints edge cases and testable I/O where relevant.
- Use LLMs as a power tool. Prompt LLMs to draft outlines generate variants sanity-check solutions and catch inconsistencies then verify and polish.
- Keep content fresh. Triage what to update or retire based on product direction user feedback internal pool of interview experiences and performance metrics (answer rate saves time-to-completion).
- Ship without hand-holding. Plan your own weekly pipeline; identify gaps; propose new questions/collections aligned with product strategy.
- Tag & structure. Ensure consistent taxonomy (topic subtopic difficulty company/role) metadata and searchability.
- Partner with Product. Align priorities with the roadmap and surface insights from learner behavior.
Requirements:
- 2 years of experience relevant to the role
- Strong technical writing and synthesizing skills.
- Strong AI skills and knowledge of context engineering prompt engineering and building AI agents and workflows
- Working Python (basic intermediate): data types control flow functions simple algorithms; able to read/validate solutions.
- Working SQL (basic intermediate): SELECT/JOINs GROUP BY CASE window functions at a minimum; can sanity-check queries and expected outputs.
- LLM fluency: comfortable crafting prompts using tools to draft/verify and knowing where human review is essential.
- Editorial judgment: can spot ambiguity leakage or trivia; can rewrite to be clear fair and interview-realistic.
- Self-management: you plan your week triage the backlog communicate status and ask for direction only when it truly changes scope.
- Tool comfort: Markdown and basic version control (or willingness to learn); can work from a content CMS/workboard.
Nice to have
- Experience interviewing or being interviewed for data/ML/analytics roles
- Light pandas or NumPy familiarity for Python questions
- Understanding of SEO basics for educational content
- Experience with tagging taxonomies and content QA workflows
Position: Technical WriterWorking Hours: Monday to Friday 5:00 AM - 2:00 PM Pacific TimeAbout the role:The clients company helps candidates practice with real interview questions. Theyre looking for a self-directed Technical Writer/Content Editor to maintain and improve their interview-question libr...
Position: Technical Writer
Working Hours: Monday to Friday 5:00 AM - 2:00 PM Pacific Time
About the role:
The clients company helps candidates practice with real interview questions. Theyre looking for a self-directed Technical Writer/Content Editor to maintain and improve their interview-question library keeping questions accurate fresh well-tagged and genuinely engaging to solve. You dont need to be a deep expert in every domain but you do need enough Python/SQL fluency and product sense to know when something is correct unclear or outdated and to fix it quickly.
Responsibilities:
- Own the question bank. Review edit and publish interview questions and solutions across Data Science Analytics ML/AI and Data Engineering categories.
- Raise quality. Rewrite unclear prompts/solutions standardize difficulty and tags add hints edge cases and testable I/O where relevant.
- Use LLMs as a power tool. Prompt LLMs to draft outlines generate variants sanity-check solutions and catch inconsistencies then verify and polish.
- Keep content fresh. Triage what to update or retire based on product direction user feedback internal pool of interview experiences and performance metrics (answer rate saves time-to-completion).
- Ship without hand-holding. Plan your own weekly pipeline; identify gaps; propose new questions/collections aligned with product strategy.
- Tag & structure. Ensure consistent taxonomy (topic subtopic difficulty company/role) metadata and searchability.
- Partner with Product. Align priorities with the roadmap and surface insights from learner behavior.
Requirements:
- 2 years of experience relevant to the role
- Strong technical writing and synthesizing skills.
- Strong AI skills and knowledge of context engineering prompt engineering and building AI agents and workflows
- Working Python (basic intermediate): data types control flow functions simple algorithms; able to read/validate solutions.
- Working SQL (basic intermediate): SELECT/JOINs GROUP BY CASE window functions at a minimum; can sanity-check queries and expected outputs.
- LLM fluency: comfortable crafting prompts using tools to draft/verify and knowing where human review is essential.
- Editorial judgment: can spot ambiguity leakage or trivia; can rewrite to be clear fair and interview-realistic.
- Self-management: you plan your week triage the backlog communicate status and ask for direction only when it truly changes scope.
- Tool comfort: Markdown and basic version control (or willingness to learn); can work from a content CMS/workboard.
Nice to have
- Experience interviewing or being interviewed for data/ML/analytics roles
- Light pandas or NumPy familiarity for Python questions
- Understanding of SEO basics for educational content
- Experience with tagging taxonomies and content QA workflows
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