Skill Profile

Text Classification

Embeddings, fine-tuning, multi-label classification, few-shot learning, benchmarks

Machine Learning & AI Natural Language Processing

Roles

where this skill appears

Levels

structured growth path

Mandatory requirements

the other 0 optional

Machine Learning & AI

Natural Language Processing

3/17/2026

Choose your current level and compare expectations. The items below show what to cover to advance to the next level.

What is Expected at Each Level

The table shows how skill depth grows from Junior to Principal. Click a row to see details.

Role	Required	Description
NLP Engineer	Required	Knows text classification basics: bag-of-words, TF-IDF, basic classifiers. Trains simple models for text categorization, spam filtering. Evaluates via accuracy, F1-score.

Role	Required	Description
NLP Engineer	Required	Independently develops text classification systems: fine-tuning BERT/RoBERTa, zero-shot classification via LLM, multi-label classification. Works with imbalanced datasets.

Role	Required	Description
NLP Engineer	Required	Designs production text classification systems: hierarchical classification, dynamic taxonomy, continual learning. Optimizes for high throughput and low latency in production.

Role	Required	Description
NLP Engineer	Required	Defines text classification strategy for the team. Establishes taxonomy management processes, evaluation standards, and architectural decisions for classification-based NLP products.

Role	Required	Description
NLP Engineer	Required	Shapes enterprise text classification strategy. Defines unified taxonomy, cross-domain classification approaches, and standards for all classification-based NLP products.

Junior 1 requirements

NLP Engineer
Required

Knows text classification basics: bag-of-words, TF-IDF, basic classifiers. Trains simple models for text categorization, spam filtering. Evaluates via accuracy, F1-score.

Middle 1 requirements

NLP Engineer
Required

Independently develops text classification systems: fine-tuning BERT/RoBERTa, zero-shot classification via LLM, multi-label classification. Works with imbalanced datasets.

Senior 1 requirements

NLP Engineer
Required

Designs production text classification systems: hierarchical classification, dynamic taxonomy, continual learning. Optimizes for high throughput and low latency in production.

Lead / Staff 1 requirements

NLP Engineer
Required

Defines text classification strategy for the team. Establishes taxonomy management processes, evaluation standards, and architectural decisions for classification-based NLP products.

Principal 1 requirements

NLP Engineer
Required

Shapes enterprise text classification strategy. Defines unified taxonomy, cross-domain classification approaches, and standards for all classification-based NLP products.

Loading comments...