We are looking for a Senior Machine Learning Engineer with a strong background in data science and software engineering to join us in Cyprus, working from our office in a flexible and hybrid work setup.

As a Machine Learning Engineer you will develop and deploy machine learning models, work with large datasets and collaborate with cross-functional teams to solve business problems.

This position is integral to one of our projects in the clients Finance IT area focusing on the integration component of their finance landscape. If you´re ready to leverage your skills and perspective to make a significant impact, apply now and help us transform our data capabilities in the finance and insurance industries.

#LI-DNI

Responsibilities
- Be responsible for the transition of machine learning algorithms to production environment and integration with enterprise ecosystem
- Design, create, maintain, troubleshoot and optimize the complete end-to-end machine learning lifecycle
- Write specifications, documentation and user guides for developed solutions
- Build frameworks for data scientists to accelerate the development of production-grade machine learning models
- Collaborate with data scientists and engineering team to optimize the performance of ML pipeline
- Constant improvement of SDLC practices
- Establish and configure CI/CD/CT processes
- Design and maintain ML models continuous training
- Provide capabilities for early detection of various drifts (data, concept, schema, etc.)
- Promote and support MLOps practices

Requirements
- 5+ years experience as ML engineer or Data Engineer of designing, building and deploying production applications and data pipelines
- Strong knowledge and experience in Python development
- Deep understanding of Python ML ecosystem (PyTorch, TensorFlow, NumPy, Pandas, Sklearn, XGBoost, etc.)
- Hands-on experience in implementation of Data Products
- Deep understanding of data preparation and feature engineering
- Understanding of Apache Spark Ecosystem (Spark SQL, MLlib/Spark ML)
- Deep hands-on experience with implementation of SDLC best practices in complex IT projects and with data processing paradigms
- Knowledge and experience in computer science disciplines such as data structures, algorithms, and software design patterns
- Experience with some of the MLOps related platform/technology such as AWS SageMaker, Azure ML, GCP Vertex AI/AI Platform, Databricks MLFlow, Kubeflow, Airflow, Argo Workflow, TensorFlow Extended (TFX), etc
- Experience with basic software engineering tools, e.g., git, CI/CD environment (such as Jenkins or Buildkite), PyPi, Docker, Kubernetes, unit testing and general object-oriented design
- Fluent English language knowledge

We offer
- Private healthcare insurance
- Regular performance assessments
- Family friendly initiatives
- Corporate Programs including Employee Referral Program with rewards
- Learning and development opportunities including in-house training and coaching, professional certifications, over 22,000 courses on LinkedIn Learning Solutions and much more
- *All benefits and perks are subject to certain eligibility requirements