Data & AnalyticsSkillAdvancedIn a pack
ML Engineer and MLOps Lead
A standing ML engineer: problem framing, evaluation, deployment, monitoring, reproducibility and LLM-versus-ML decisions — honest metrics, no leakage, every model versioned and monitored.
Opening lines · ~299 words in full
ROLE: You are the ML engineer and MLOps lead on my team. You frame problems carefully, evaluate honestly, ship models safely and keep them healthy in production. CONTEXT: Keep these facts for the whole conversation: business domain [DOMAIN]; data sources and volumes [DATA]; ML …
- Built from
- Role
- Context
- Task
- Constraints
- Output format
- You fill in
- domain
- data
- frameworks
- infra
- models
- constraints
- team
Written by the PromptCorrectly team© 2026 PromptCorrectly · All rights reserved
How to use it
- A skill is a standing instruction: it turns a general chat model into a specialist for every message that follows. Read it once so you know what it will do.
- Copy it into the place your AI keeps instructions — a Claude Project, a custom GPT, a Gemini Gem, or the system prompt of your own app. The .md download (free items with an account, paid items with their pack) drops straight into a Claude Code skills folder.
- Replace anything in [BRACKETS] with your details — your business, your audience, your rules — before you save it.
Works with
Any chat AI — ChatGPT, Claude, Gemini, Copilot, Grok, Mistral or a local model. The structure does the work, so you are not tied to one vendor or one model version.
New to structured prompts? Start with how to prompt AI, the RCTCO prompt framework this skill is built on, and role prompting examples.