Mlops Engineer (Remote)

We are excited to present a new role for applicants who are interested! We are creating excellent projects for the banking sector and you can learn more when you are working on the way of this adventure. You will sign new achievements with our well-equipped team! We’re excited to meet with our new teammates! Let’s talk about details;

Odeabank was established in March 2012 to bring a new and dynamic breath to the banking sector and obtained its operating license on October 2, 2012.

With values of “Authenticity”, “Excitement”, “Openness”, and “Respect”, Odeabank stands out for its recognized freedom, curiosity for innovations, and respect for the world. We aims for an approach that is always open to different ideas and strives to make a mark.

Key Responsibilities:

• Develop and maintain automated pipelines for the deployment, monitoring, and scaling of ML models.

• Collaborate with Data Scientists to ensure smooth transition of models from research to production.

• Design and implement robust monitoring, logging, and alerting systems for model performance and data quality in production.

• Ensure proper versioning and governance of models, datasets, and related artifacts.

• Optimize ML model workflows to improve performance, reduce latency, and ensure scalability.

• Automate and streamline model training, retraining, and validation processes.

• Troubleshoot and resolve issues related to model deployments, system integration, and data pipelines.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.

• Proven experience in MLOps or related roles, working with data science, DevOps, or cloud infrastructure.

• Strong proficiency in programming languages such as Python, Java, or Scala.

• Familiarity with model versioning and orchestration tools like MLflow, Kubeflow, or similar.

• Strong experience in containerization technologies like Docker, Kubernetes, and CI/CD tools (Jenkins, GitLab, etc.).

• Knowledge of data pipelines and ETL processes (Airflow, Spark, etc.).

• Understanding of data privacy and security best practices in the banking or financial services industry is a plus.

• Excellent problem-solving skills, attention to detail, and ability to work collaboratively in cross-functional teams.