Senior AI/ML Engineer — End-to-End GenAI & MLOps

Primeit; Lisboa; On-site; EUR 13,000 - 22,000; Full time

Benefits offered by this job

Meal allowance

Flex benefits

Job summary

PrimeIT is seeking a Senior AI/ML Engineer to design, develop, and productionize end-to-end AI/ML solutions in a Portugal-based project. You will own the AI/ML lifecycle, deploy and monitor models, and build scalable data pipelines within an Agile team.

The ideal candidate has hands-on Python expertise, strong AWS experience (S3, SageMaker, Bedrock, Lambda, API Gateway, OpenSearch), and solid knowledge of MLOps tools like Docker, Kubernetes, Airflow, MLflow, GitLab, and HuggingFace.

Qualifications

• Experience in AI/ML with real-world implementations.
• Advanced proficiency in Python.
• Hands-on experience with AWS services (S3, SageMaker, Bedrock, Lambda, API Gateway, OpenSearch).
• Strong knowledge of MLOps/DevOps tools (Docker, Kubernetes, Airflow, MLflow, GitLab, HuggingFace).
• Experience with ML frameworks (Scikit-learn, TensorFlow, PyTorch, Transformers) and Generative AI concepts, including vector databases (e.g., Redis, OpenSearch).

Responsibilities

• Design, develop, and implement end-to-end AI/ML solutions, from modeling to production.
• Manage AI/ML use cases lifecycle, including deployment, monitoring, and optimization.
• Build and industrialize data pipelines and ML workflows for scalable environments.
• Contribute to projects involving Generative AI and multi-agent systems.
• Collaborate with cross-functional teams in an Agile environment.

Skills

AI/ML

Python

AWS services

MLOps/DevOps

Transformers

PyTorch

TensorFlow

Scikit-learn

HuggingFace

Kubernetes

Airflow

MLflow

GitLab

Vector databases

Tools

Docker

Kubernetes

Airflow

MLflow

GitLab

HuggingFace

Job description

PrimeIT is seeking a Senior AI/ML Engineer to design, develop, and productionize end-to-end AI/ML solutions in a Portugal-based project. You will own the AI/ML lifecycle, deploy and monitor models, and build scalable data pipelines within an Agile team.

The ideal candidate has hands-on Python expertise, strong AWS experience (S3, SageMaker, Bedrock, Lambda, API Gateway, OpenSearch), and solid knowledge of MLOps tools like Docker, Kubernetes, Airflow, MLflow, GitLab, and HuggingFace.