AI/ML Engineer: Build Scalable Enterprise AI Solutions

Quik Hire Staffing; France; Sur place; EUR 55 000 - 90 000; Plein temps

Résumé du poste

We are seeking an AI/ML Engineer to join a leading software development organization, working on a full-time basis to design, develop, and deploy ML models addressing complex business challenges. You will collaborate with cross-functional teams to integrate AI into production systems.

The role emphasizes building models with Python using TensorFlow or PyTorch, data preprocessing, and deploying models in production, with a strong focus on cloud platforms and MLOps practices.

Qualifications

• Proficient in Python with ML libraries such as TensorFlow or PyTorch.
• Experience with data preprocessing, feature engineering, and model evaluation.
• Knowledge of cloud platforms (AWS, GCP, or Azure) for deployment and scaling.
• Familiarity with MLOps practices, including CI/CD pipelines for ML.
• Strong problem-solving skills translating business requirements into technical solutions.

Responsabilités

• Design, develop, and optimize machine learning models using Python and relevant frameworks.
• Preprocess, clean, and transform large datasets to prepare for training.
• Deploy and monitor ML models in production environments.
• Collaborate with software engineers to integrate AI solutions into existing infrastructure.
• Conduct performance benchmarking and model validation to ensure accuracy and efficiency.

Connaissances

Python

TensorFlow

PyTorch

Data preprocessing

Cloud platforms

MLOps CI/CD

Problem-solving

Outils

AWS

GCP

Azure

CI/CD tools

Description du poste

We are seeking an AI/ML Engineer to join a leading software development organization, working on a full-time basis to design, develop, and deploy ML models addressing complex business challenges. You will collaborate with cross-functional teams to integrate AI into production systems.

The role emphasizes building models with Python using TensorFlow or PyTorch, data preprocessing, and deploying models in production, with a strong focus on cloud platforms and MLOps practices.