Skill Profile

Neural Network Architectures

This skill defines expectations across roles and levels.

Machine Learning & AI Deep Learning

Roles

where this skill appears

Levels

structured growth path

Mandatory requirements

the other 10 optional

Machine Learning & AI

Deep Learning

2/22/2026

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
Data Scientist		Understands basic neural network architectures: MLP, CNN, RNN/LSTM and their applications. Knows components: layers, activations, optimizers, loss functions. Creates simple architectures in PyTorch/Keras for typical classification and regression tasks.
LLM Engineer		Knows main neural network architectures: MLP, CNN, RNN, Transformer. Understands Transformer architecture specifics for language models: self-attention, positional encoding, feed-forward layers.

Role	Required	Description
Data Scientist		Designs and implements modern architectures: Transformers, U-Net, ResNet, EfficientNet. Applies attention mechanisms, skip connections, residual learning. Selects optimal architecture based on task, data, and production requirements.
LLM Engineer		Independently analyzes and modifies neural network architectures for LLM tasks: adapter layers, custom attention patterns, mixture of experts. Implements architectural modifications in PyTorch.

Role	Required	Description
Data Scientist		Designs custom architectures for specific business tasks. Applies neural architecture search (NAS), progressive growing, modular design. Optimizes architectures for latency/accuracy trade-off in production deployment.
LLM Engineer		Designs custom neural network architectures for LLM: efficient attention mechanisms, sparse transformers, multi-modal architectures. Conducts ablation studies to optimize architectural decisions.

Role	Required	Description
Data Scientist		Defines architectural guidelines for the team's deep learning projects. Establishes model zoo with pre-validated architectures. Coordinates research directions and evaluation of new architectural approaches for production use.
LLM Engineer		Defines architectural standards for the LLM team. Establishes architecture selection guidelines, conducts architectural decision reviews, coordinates R&D on new architectures.

Role	Required	Description
Data Scientist		Shapes neural architecture development strategy for the organization. Defines research direction, evaluates state-of-the-art. Publishes research on new architectures and shapes the organization's scientific leadership.
LLM Engineer		Shapes organizational architectural research strategy. Defines R&D directions for neural architectures, evaluates state-of-the-art approaches, and mentors leads on architectural design.

Junior 2 requirements

Data Scientist

Understands basic neural network architectures: MLP, CNN, RNN/LSTM and their applications. Knows components: layers, activations, optimizers, loss functions. Creates simple architectures in PyTorch/Keras for typical classification and regression tasks.
LLM Engineer

Knows main neural network architectures: MLP, CNN, RNN, Transformer. Understands Transformer architecture specifics for language models: self-attention, positional encoding, feed-forward layers.

Middle 2 requirements

Data Scientist

Designs and implements modern architectures: Transformers, U-Net, ResNet, EfficientNet. Applies attention mechanisms, skip connections, residual learning. Selects optimal architecture based on task, data, and production requirements.
LLM Engineer

Independently analyzes and modifies neural network architectures for LLM tasks: adapter layers, custom attention patterns, mixture of experts. Implements architectural modifications in PyTorch.

Senior 2 requirements

Data Scientist

Designs custom architectures for specific business tasks. Applies neural architecture search (NAS), progressive growing, modular design. Optimizes architectures for latency/accuracy trade-off in production deployment.
LLM Engineer

Designs custom neural network architectures for LLM: efficient attention mechanisms, sparse transformers, multi-modal architectures. Conducts ablation studies to optimize architectural decisions.

Lead / Staff 2 requirements

Data Scientist

Defines architectural guidelines for the team's deep learning projects. Establishes model zoo with pre-validated architectures. Coordinates research directions and evaluation of new architectural approaches for production use.
LLM Engineer

Defines architectural standards for the LLM team. Establishes architecture selection guidelines, conducts architectural decision reviews, coordinates R&D on new architectures.

Principal 2 requirements

Data Scientist

Shapes neural architecture development strategy for the organization. Defines research direction, evaluates state-of-the-art. Publishes research on new architectures and shapes the organization's scientific leadership.
LLM Engineer

Shapes organizational architectural research strategy. Defines R&D directions for neural architectures, evaluates state-of-the-art approaches, and mentors leads on architectural design.

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