Perfil de habilidad

Transformer Architecture

Esta habilidad define expectativas en roles y niveles.

Machine Learning & AI LLM & Generative AI

Roles

donde aparece esta habilidad

Niveles

ruta de crecimiento estructurada

Requisitos obligatorios

los otros 5 opcionales

Machine Learning & AI

LLM & Generative AI

22/2/2026

Selecciona tu nivel actual y compara las expectativas.

Qué se espera en cada nivel

La tabla muestra cómo crece la profundidad desde Junior hasta Principal.

Rol	Obligatorio	Descripción
LLM Engineer		Knows Transformer basics: self-attention, multi-head attention, positional encoding, feed-forward layers. Understands encoder-decoder and decoder-only architectures and their application in LLM.

Rol	Obligatorio	Descripción
LLM Engineer		Independently analyzes and modifies Transformer architectures: RoPE, ALiBi, GQA, SwiGLU. Understands architectural differences between GPT, LLaMA, Mistral and their impact on performance.

Rol	Obligatorio	Descripción
LLM Engineer		Designs custom Transformer modifications: efficient attention (FlashAttention, sliding window), custom positional encoding, architectural search. Implements and evaluates novel architectural solutions.

Rol	Obligatorio	Descripción
LLM Engineer		Defines Transformer architecture standards for the LLM team. Establishes guidelines for architecture selection, new approach evaluation, R&D directions. Coordinates architectural experiments.

Rol	Obligatorio	Descripción
LLM Engineer		Shapes enterprise Transformer R&D strategy. Defines long-term architectural directions, evaluates emerging architectures (Mamba, RWKV), and plans transitions between architecture generations.

Junior 1 requisitos

LLM Engineer

Knows Transformer basics: self-attention, multi-head attention, positional encoding, feed-forward layers. Understands encoder-decoder and decoder-only architectures and their application in LLM.

Middle 1 requisitos

LLM Engineer

Independently analyzes and modifies Transformer architectures: RoPE, ALiBi, GQA, SwiGLU. Understands architectural differences between GPT, LLaMA, Mistral and their impact on performance.

Senior 1 requisitos

LLM Engineer

Designs custom Transformer modifications: efficient attention (FlashAttention, sliding window), custom positional encoding, architectural search. Implements and evaluates novel architectural solutions.

Lead / Staff 1 requisitos

LLM Engineer

Defines Transformer architecture standards for the LLM team. Establishes guidelines for architecture selection, new approach evaluation, R&D directions. Coordinates architectural experiments.

Principal 1 requisitos

LLM Engineer

Shapes enterprise Transformer R&D strategy. Defines long-term architectural directions, evaluates emerging architectures (Mamba, RWKV), and plans transitions between architecture generations.

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