AI/ML Engineer — NLP, LLMs & Agentic AI

Altia; Vigo; On-site; EUR 70,000 - 120,000; Full time

Benefits offered by this job

High-impact project

Collaborative work environment

Career Plan

Training Plan

Flexible Remuneration

Job summary

Altia is seeking an AI/ML Engineer to design, develop, and maintain AI/ML solutions with a strong emphasis on NLP, LLMs, agentic AI, and data-driven applications. You will contribute to an international project supporting European institutions, delivering intelligent services across public-sector use cases.

Work with Python-based architectures, LangChain and other frameworks to implement scalable AI services, data pipelines, and MLOps with bias mitigation and governance considerations.

Qualifications

• Experience designing and delivering NLP/LLM driven AI solutions.
• Strong Python data science stack and model lifecycle knowledge.
• Experience with cloud AI services and MLOps practices.
• Familiarity with responsible AI, bias mitigation and governance.

Responsibilities

• Design, develop, and maintain AI/ML solutions with emphasis on NLP and LLMs.
• Build agentic AI services and applications using modern frameworks.
• Handle data ingestion, quality, governance across data lakes and stores.
• Deploy and monitor models on cloud platforms with CI/CD and observability.
• Integrate AI capabilities into existing applications via REST services.
• Ensure responsible AI, governance, and regulatory compliance.

Skills

Python

NLP

ML

LLMs

R

Pandas

Scikit-learn

TensorFlow

PyTorch

SpaCy

NLTK

Retrieval-Augmented Generation

Tools

LangChain

LlamaIndex

Semantic Kernel

AWS Bedrock

SageMaker

Azure AI Studio

Azure ML

MLflow

Kubeflow

REST APIs

Job description

Altia is seeking an AI/ML Engineer to design, develop, and maintain AI/ML solutions with a strong emphasis on NLP, LLMs, agentic AI, and data-driven applications. You will contribute to an international project supporting European institutions, delivering intelligent services across public-sector use cases.

Work with Python-based architectures, LangChain and other frameworks to implement scalable AI services, data pipelines, and MLOps with bias mitigation and governance considerations.