ML Engineer, 4+ years experience

General

We are looking for Machine Learning Engineers to join our client Data & AI team and contribute to the design, development, and deployment of scalable ML solutions across the organization.

 

Responsibilities/Activities

• Research, develop, and enhance machine learning models aligned with business objectives
• Analyze large structured and unstructured datasets to identify patterns, test hypotheses, and support model development through strong analytical work
• Ensure models are production-ready by writing clean, maintainable training and inference code, with proper monitoring, validation checks, and robust error-handling
• Collaborate with cross-functional teams to understand requirements, design ML solutions, and validate the impact of deployed models
• Build and maintain data pipelines and model deployment workflows
• Optimize and improve the performance and scalability of ML models running in cloud environments
• Monitor and maintain ML models in production to ensure reliability and optimal performance
• Contribute to improving ML infrastructure, automation, and end-to-end model lifecycle practices

Requirements

Technical

• At least 4 years of previous experience in a similar role
• Solid experience with modern ML frameworks: TensorFlow, PyTorch
• Working experience with ML experiment tracking tools: MLflow, W&B, DVC
• Proven experience in building, training, and deploying ML models (batch or real-time)
• Solid ability to write clean, well-structured, and testable Python code
• Experience with relational databases and distributed data systems
• Good knowledge of Big Data tools (e.g. Spark, Dask) and distributed data processing
• Familiarity with cloud platforms, containerization, and orchestration tools
• Solid understanding of supervised, unsupervised, and deep learning techniques
• Good understanding of Agile/Scrum methodologies

Education

• University degree in Computer Science, Data Science, or another related field

Others

• Good level of English (oral and written)
• Strong analytical and problem-solving skills
• Ability to learn quickly and adapt to new technologies
• Comfortable working under tight deadlines

Nice to have requirements

• Experience with infrastructure-as-code (Terraform, CloudFormation)
• Experience with end-to-end MLOps practices