Machine Learning Engineer
Ernst and Young3 days ago
Athens, GreeceMid Level
Responsibilities
- Collaborate with data scientists on machine learning model integration and production deployment.
- Set up infrastructure and tools for deploying and monitoring machine learning models.
- Manage cloud resources and optimize performance for machine learning workloads.
- Implement automated testing and deployment pipelines.
- Build and maintain data pipelines for preprocessing and transformation.
- Monitor model performance and overall system health.
- Ensure data security and compliance, and document processes and best practices.
- Stay current with MLOps and AIOps developments and contribute to EY innovation.
- Provide technical advice to clients and support engagements in Greece and abroad.
Requirements
- Bachelor’s or master’s degree in computer science, data science, engineering, or a related field.
- Experience in AIOps, MLOps, or system administration.
- Demonstrated experience deploying machine learning models into production environments.
- Experience with cloud platforms such as Amazon Web Services, Microsoft Azure, Google Cloud Platform, or Cloudera.
- Understanding of cloud resource utilization for deploying and scaling machine learning models.
- Strong analytical, problem-solving, critical-thinking, interpersonal, and technical-writing skills.
- Preferred: proficiency in DevOps practices and automated software testing.
- Preferred: knowledge of Docker, Kubernetes, MLflow, Kubeflow, Synapse Analytics, or SageMaker.
- Preferred: understanding of machine learning pipelines, model monitoring, deployment infrastructure, servers, storage systems, networking, and resource provisioning.
- Advanced technical writing skills in Greek and English and willingness to travel or work abroad for international projects.
Benefits
- Hybrid working arrangement across EY offices in Athens, Patras, Thessaloniki, and Crete, based on preferences and team needs.
- Access to educational platforms, EY Badges, EY Degrees, certification support, coaching, feedback, and international projects.
- Exposure to EY’s GenAI ecosystem and advanced AI tools.
- Technological equipment, ticket restaurant vouchers, private health and life insurance, income protection, and an EY benefits club card.
- Flexible initiatives including short Fridays, Flex Day, and Together Day.
- Opportunities for volunteering, sustainable practices, and societal impact.
- Inclusive and diverse workplace culture.
Tech Stack
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