mlops/aiops engineer

We are looking for an experienced MLOps/AIOps Engineer to help design, implement, and scale machine learning infrastructure and operations. This is a hands-on engineering role focused on enabling robust ML workflows and seamless collaboration between data science and engineering teams.

The key responsibilities of this role will include:

• Design and maintain scalable ML pipelines for training, evaluation, deployment, and monitoring

• Build and manage CI/CD workflows tailored to ML use cases

• Automate model release, versioning, and rollback strategies

• Integrate monitoring and observability tools for model and data performance

• Work with platform teams to provision and manage GPU/CPU infrastructure

• Drive best practices in reproducibility, compliance, and ML lifecycle management

To be successful at this role you need the following (hard and soft skills):

• 3+ years in MLOps, ML Engineering, or a similar role in production environments

• Proficiency in Python and scripting (Bash, PowerShell)

• Strong skills in containerization and deployment (Docker, Kubernetes, REST APIs), with CI/CD integration (e.g., GitHub Actions, Azure DevOps)

• Experience with model lifecycle tools (e.g., MLflow Model Registry, Azure ML), including versioning, stage transitions, and rollback

• Familiarity with model monitoring and drift detection using platforms like Evidently AI

• Experience with monitoring tools (Grafana, Prometheus)

• Experience with infrastructure-as-code tools (e.g., Terraform) for scalable ML environments

• Working knowledge with ML orchestration tools (e.g., Airflow, Prefect)

• Strong communication skills with the ability to effectively collaborate with cross-functional teams, including data scientists, cloud/platform engineers, and software developers, to deliver robust and scalable ML solutions

• Demonstrated ability to write high-quality, maintainable, and scalable code, with a strong focus on system performance and reliability

Nice to Have

• Exposure to Databricks for scalable data processing and ML workflows

• Familiarity with Kafka for real-time data streaming

• Experience with feature stores (e.g., Feast or Tecton) for managing ML features across training and serving

• Relevant certifications such as Azure AI Engineer Associate, Azure DevOps Engineer Expert, or Databricks Certified Machine Learning Professional.

What’s in it for You?

At Grant Thornton Greece, we believe that great work deserves great rewards! Here’s what you can look forward to:

• 🌈 Diverse and inclusive workplace

• 🏋️‍♂️ Friendly, Dynamic Working environment

• 💰 Competitive Salary & Bonus

• 🩺 Insurance Program for all GT members

• 👩‍🏫 Fully funded Training & Professional Qualifications

• 🏖 Extra Days-off: August Freedays, Volunteering Days, Early leave days

• 🏃🏽‍♂️ Corporate Sports Teams (e.g., Running, Basketball, Volleyball)

• 🎁 Exclusive Discounts: Special offers and discounts for employees

• 🚗 Company Car (depending on job level)