Senior Machine Learning Engineer

This is a fully remote position, open to applicants in Greece.

📋 Description

• Take charge of the reliability, scalability, and automation of machine learning pipelines.

• Utilize Docker to containerize pipeline services and deploy them on AWS.

• Create scalable, event-driven execution for data preparation, model training, and prediction tasks.

• Develop and enhance CI/CD pipelines using GitHub Actions.

• Enhance observability through effective logging, metrics, and alerting mechanisms.

• Fortify the model lifecycle with reproducible training environments, experiment tracking, model versioning, and deployment strategies.

• Advance and scale production pipelines to serve customer needs.

• Architect cloud solutions and lead platform modernization efforts from concept to production.

• Manage initiatives from start to finish, delivering incrementally without interfering with live systems.

• Collaborate with data scientists and DevOps engineers across the technology stack.

• Optimize training, evaluation, and deployment workflows.

⛳️ Requirements

• Over 5 years of experience managing production Python systems.

• Strong foundation in software engineering principles: testing, version control, code review, and CI/CD practices.

• Practical experience with Docker, including Dockerfiles, multi-stage builds, and debugging production containers.

• Comprehensive AWS experience, including EC2, ECS, S3, EFS, CloudWatch, and IAM.

• Proven track record in developing automated build, test, and deployment pipelines with GitHub Actions or similar tools.

• Familiarity with MongoDB and PostgreSQL, including secure service connections in containerized settings.

• Experience in supporting the machine learning lifecycle in production, including tools like MLflow or similar, reproducible training pipelines, and model deployment.

• Knowledge of modern Python environment and configuration tools such as uv, pydantic, and Hydra/OmegaConf.

• Experience with workflow orchestrators like SageMaker Pipelines or Prefect.

• Proficient with TensorFlow, scikit-learn, LightGBM, and geopandas.

• Familiarity with geospatial data or GIS tools is advantageous, though not mandatory.

• Commitment to cost efficiency, including optimizing compute resources and selecting suitable storage options.

🏝️ Benefits

• Full-time employment.

• Fully remote work arrangement.

• Opportunity to work with a multi-award-winning AI solution utilized by water utilities and municipalities globally.