1 year ago
Athens, GreeceSenior
Responsibilities
- Build robust, scalable, end-to-end machine learning pipelines and operationalize machine learning solutions for credit risk management.
- Provide technical expertise and guidance on ML engineering, MLOps, workflow scalability, stability, accuracy, speed, efficiency, testing, and code quality.
- Design and develop microservices and tools supporting the machine learning lifecycle, including scalable real-time services used globally.
- Design, develop, maintain, tune, and refactor large-scale Spark jobs using PySpark and Scala.
- Build and manage CI/CD pipelines with Jenkins and develop automation scripts using Python or Bash.
- Develop and deploy scalable Airflow pipelines supporting the machine learning lifecycle.
- Perform data exploration and analysis for machine learning proof-of-concepts and partner with engineering and credit risk teams on business solutions.
- Improve the feature engineering engine and drive continuous improvements in the development lifecycle.
Requirements
- Bachelor's or master's degree in Electrical Engineering, Computer Science, or Informatics.
- 5+ years of industry experience in Machine Learning Engineering and MLOps.
- Solid understanding of machine learning concepts and MLOps.
- Proficiency in Python and PySpark, or Scala and Java.
- Strong knowledge of the Hadoop ecosystem and proficiency in SQL and Linux.
- Strong knowledge of end-to-end API development and deployment.
- Proficiency in building and managing Dockerized applications.
- Experience with workflow orchestration tools such as Airflow or similar tools.
- Familiarity with CI/CD best practices and the ability to learn and adapt to emerging tools and frameworks.
- Ability to meet tight deadlines, work under pressure, and maintain strict attention to detail.
Benefits
- Hybrid workplace with flexible remote working.
- Competitive remuneration package and performance-based bonus scheme.
- Extra day off on the employee's birthday.
- Comprehensive private healthcare insurance.
- All required technology equipment for work.
- Multicultural working environment, career development, continuous training, and access to online training platforms.
- CSR activities, festive events, on-site restaurant with varied meal options, and wellbeing activities including yoga and access to a squash court.
Tech Stack
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