machine learning engineer.

• Automate model training, evaluation, and deployment processes in development environments.
• Build and maintain CI/CD pipelines specifically for model training and evaluation.
• Ensure proper documentation for all tools, CI/CD pipelines, containers, and reusable code to maintain clarity and ease of use for future team members.
• Document best practices and guidelines for integrating new models into the workflow.
• Support continuous model retraining and monitoring efforts in collaboration with data scientists.
• Extend and maintain available containers that are compatible with different stages of deployment (training, testing, etc.).
• Work closely with the software team responsible for putting model artifacts into the production pipeline, ensuring a smooth handoff of model outputs.
• Maintain and continuously refactor reusable training/evaluation code, ensuring modularity and scalability.
• Design and implement tools to support ML workflows, such as monitoring tools or visualization aids.

• Bachelor’s or Master’s degree in Computer Science, Engineering, or Data Science.
• 5+ years of experience in machine learning engineering.
• Proven experience in building, maintaining, and automating CI/CD pipelines for machine learning projects.
• Experience with model deployment and monitoring using AWS services.
• Familiarity with cloud-based machine learning workflows and infrastructure.
• Strong proficiency in Python, Bash, and Shell scripting for automation.
  Proficient in frameworks like TensorFlow, PyTorch, and Scikit-learn for model training and evaluation.
• Hands-on experience with AWS services: Amazon S3, Amazon SageMaker, AWS Lambda, Amazon ECS/EKS.
  Experience with Docker for the containerization of ML workloads.

Nice to Haves:

• Knowledge of AWS Step Functions for orchestrating serverless workflows.
• Familiarity with Terraform for managing AWS infrastructure as code.
• Experience with distributed training.

• Chance to join a growing organization
• Annual bonus, (equal to a 13th month’s payment)
• Cafeteria
• 2 days of home office every week
• Private health insurance
• Work in a truly international environment

Ildikó Mező-Mészáros
ildiko.mezo-meszaros@randstad.hu