What is machine-learning-engineer?

A guide for building machine-learning systems from raw data through deployment. It covers data preparation, model training and evaluation, operational tooling, and production use of models including deep-learning and language models.

Building data pipelines, training and evaluating models, preparing models for production, and working with tools such as scikit-learn, XGBoost, PyTorch, transformers, LoRA, or QLoRA.

It brings the separate stages of an ML project into one working process. It helps with both traditional models and newer neural-network or language-model systems.

machine-learning-engineer — Skill by jshearin01/agent-skills

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add jshearin01/agent-skills --skill machine-learning-engineer

Clone the repo

git clone --depth 1 https://github.com/jshearin01/agent-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/jshearin01/agent-skills/machine-learning-engineer/github.svg)](https://agentmods.dev/skills/jshearin01/agent-skills/machine-learning-engineer)

Your own site

<a href="https://agentmods.dev/skills/jshearin01/agent-skills/machine-learning-engineer"><img src="https://agentmods.dev/badge/skills/jshearin01/agent-skills/machine-learning-engineer/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/jshearin01/agent-skills/machine-learning-engineer"><img src="https://agentmods.dev/badge/skills/jshearin01/agent-skills/machine-learning-engineer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 180 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 3,032 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin unknown No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00180	$0.03032
Opus 5.5	$0.00072	$0.01213
Sonnet 5.5	$0.00036	$0.00606
Haiku 4.5	$0.00018	$0.00303

Measured 2mo ago against content hash 1d415b87ced0, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

machine-learning-engineer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

The scan reads SKILL.md. This mod also ships 4 executable files (scripts/experiment_tracking.py, scripts/feature_pipeline.py, scripts/model_evaluation.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

machine-learning-engineer/SKILL.md · 296 lines

The source is not reproduced here

No licence file

Read it on GitHub

Files

What ships with it

8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

2mo ago First seen · 296 lines · 180 tokens per session scan A 1d415b87ced0

Subscribe to this mod's changes

machine-learning-engineer is a skill published in the GitHub repository jshearin01/agent-skills (17 stars, last pushed 5mo ago), with no licence file. It adds 180 tokens to every session and 3,032 once invoked, about $0.0007 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Data and AI

machine-learning-engineer next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
machine-learning-engineerjshearin01/agent-skills	Skill	17	5mo ago	none	A	180	Claude Code, Codex
agent-platform-model-registrygoogle/skills	Skill	22k	yesterday	Apache-2.0	A	60	Claude Code, Codex
foundry-config-setupmicrosoft/agent-framework	Skill	15k	yesterday	MIT	A	65	Claude Code, Codex
google-cloud-solution-agentic-analytics-spark-knowledge-cataloggoogle/skills	Skill	22k	yesterday	Apache-2.0	A	132	Claude Code, Codex
training-checkwanshuiyin/Auto-claude-code-research-in-sleep	Skill	19k	3d ago	MIT	A	35	Claude Code
nemo-automodel-launcher-configNVIDIA/skills	Skill	3.9k	yesterday	Apache-2.0	A	30	Claude Code
finetuningmicrosoft/skills	Skill	3.2k	yesterday	MIT	A	132	Claude Code