Senior Machine Learning Engineer
iTechScope, Greece
Job Description
On behalf of our client an innovative company providing AI services for the marine industry, we are currently looking for a knowledgeable Machine-Learning Engineer to join the data analytics team.
As a Machine Learning Engineer, you will collaborate with domain experts and data engineers to research, develop and maintain machine learning models. You will be responsible for the complete ML lifecycle (MLOps) and framework as part of the analytics platform. You will support the data science development practices of the team and contribute to novel ideas around the digitalization of the maritime industry.
Your day-to-day
- Collaborate with domain experts to research, train and maintain ML Models
- Design, develop and operate scalable ML pipelines based on the infrastructure available
- Determine model performance metrics and develop monitoring solutions
- Provide best practices, guidance, and support other data scientists and ML experts
Requirements
What you will need
- Bachelor's or higher degree in Computer Engineering, Computer Science or equivalent
- 5+ years working experience in a similar position
- Experience in Machine Learning methodologies (e.g. supervised/unsupervised learning, deep learning, natural language processing)
- Experience with Spark or similar Big Data Frameworks
- Deep understanding of MLOps principles and tech stack (e.g. MLFlow)
Great to have
- Hands-on experience with Kubernetes, Docker and containerization concepts
- Familiarity with an Agile Development Methodology (Scrum)
Benefits
You will be a part of an innovative environment, where you will be able to gain more knowledge in new technologies and take the next step in your career. Your opinions and ideas will be heard, and your daily contribution will make a difference for thousands of customers globally. On top of that, a competitive package depending on your experience will be a bonus to this great experience, along with private insurance, extra benefits and the ability to work hybrid-remotely.