Machine Learning Engineer (MLOps)

TL;DR

Machine Learning Engineer (MLOps): Designing and operating production-grade machine learning systems and AI solutions for a global banking network with an accent on MLOps, scalability, and Generative AI integration. Focus on bridging the gap between experimentation and production, building scalable data pipelines, and implementing model monitoring for financial products.

Location: Hybrid in Istanbul (Vadistanbul office). Requires 2 days/week in office for 3 weeks of the month, with 1 week fully remote.

Company

A global analytics hub for ING providing AI and advanced analytics solutions to the international banking network.

What you will do

• Design, build, and maintain production-grade ML solutions and scalable data/feature pipelines.
• Operationalize models in partnership with data scientists to drive real business impact.
• Develop monitoring, alerting, and observability capabilities for ML systems.
• Improve MLOps processes, deployment standards, and CI/CD automation.
• Support the deployment and lifecycle management of Generative AI and LLM-powered applications.
• Collaborate with international stakeholders across the global analytics ecosystem.

Requirements

• Bachelor's degree or equivalent practical experience.
• 3+ years of hands-on experience in ML Engineering, MLOps, or production AI systems.
• Strong Python engineering skills and experience with distributed processing (Apache Spark).
• Proficiency with ML frameworks (Scikit-Learn, XGBoost) and experiment tracking (MLflow, Weights & Biases).
• Knowledge of software engineering best practices including testing, version control, and code reviews.
• Must be based in or be able to work from the Istanbul office.

Nice to have

• Experience with Docker, Kubernetes, OpenShift, and CI/CD pipelines.
• Familiarity with deep learning frameworks such as PyTorch or TensorFlow.
• Knowledge of model monitoring, observability, and operational performance management.
• Experience with LLM and Generative AI application deployment concepts.

Culture & Benefits

• Hybrid work model with specific remote weeks and full remote opportunities throughout August.
• Welcome leave of 14 days in the first year.
• Comprehensive health insurance for employees, spouses, and children.
• Private pension plan, meal card, and transportation allowance.
• Access to global learning platforms and English language development support.
• MultiSport membership and a vibrant, informal office atmosphere.