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Machine Learning Engineer

ING

Hybrid
Istanbul, TR
Full-time
Senior
3+ yrs
Salary not listedPosted 1mo ago

Real job — pulled straight from ING’s careers page · Verified July 14, 2026 · No reposts.

Job description

ING is hiring a Machine Learning Engineer — a full-time, based in Istanbul, TR role. Apply directly on ING's careers page below.

Machine Learning Engineer

Location: Istanbul, 34, TR

Employment Type: Full time

Are you passionate about building and operating machine learning systems that create real business impact?

At ING Analytics, you'll help bring advanced analytics and AI solutions into production environments used across ING's international network. From traditional machine learning pipelines to emerging Generative AI capabilities, you'll work on products that support decision-making, drive efficiency, and help shape the future of banking.

Role Summary

We are looking for a Senior Machine Learning / MLOps Engineer to join our Analytics Engineering ecosystem in Istanbul.

In this role, you will work closely with Data Scientists, Data Engineers, and Product Teams to design, deploy, monitor, and continuously improve production-grade machine learning systems. You will help bridge the gap between experimentation and scalable production environments while contributing to ING's growing AI and Generative AI landscape.

Your work will support analytics products including call & speech analytics, risk summarization solutions powered by Generative AI, portfolio intelligence, ESG analytics and other data-driven products used across ING. As part of ING Analytics, your solutions will contribute to systems operating across multiple countries and business domains, supporting ING's ambition to become a truly data-driven organization.

Work Model

At ING Hubs Turkiye, flexibility is more than a benefit — it's part of how we work.

Our hybrid way of working is designed to balance collaboration, innovation, and personal flexibility. Team members typically come together at our Vadistanbul office for two days per week during three weeks of the month, while one week each month is fully remote.

We also offer additional flexibility during the summer period, with remote working opportunities throughout August, allowing colleagues to spend more time where they feel most productive while staying connected to their teams.

As part of a globally distributed Analytics Engineering organization, you'll collaborate with colleagues across multiple ING locations while contributing to machine learning and AI solutions that create impact across the bank.

About the Team

Within ING, there is ING Analytics (INGA) – a major driving force behind ING's digital transformation.

By creating measurable value for ING and its customers through world-class analytics products and services, INGA helps ING become a leader in data-driven decision-making.

Among others, INGA delivers:

  • Call & Speech Analytics
  • Generative AI in Risk Summarization
  • Portfolio Performance Insights
  • Advanced ESG Data Insights
  • Cloud & On-Prem Analytics Platforms
  • Enterprise Machine Learning Solutions

ING Analytics combines deep business understanding with modern engineering practices to bring analytics products from concept to production.

About You

We hire smart people like you for your potential. Our biggest expectation is that you'll stay curious. Keep learning. Take on responsibility. In return, we'll back you to develop into an even more awesome version of yourself.

We are primarily targeting professionals with 3+ years of hands-on experience in Machine Learning Engineering, MLOps, or production AI systems. Whether you have established yourself as a senior engineer or are ready to take the next step toward greater technical ownership, you'll find opportunities to grow and make an impact in this role.

Minimum Qualifications

  • Bachelor's degree or equivalent practical experience
  • Strong Python engineering skills
  • Hands-on experience building and maintaining production ML pipelines
  • Experience with distributed data processing frameworks such as Apache Spark
  • Experience with ML frameworks such as Scikit-Learn, XGBoost, and MLflow
  • Familiarity with experiment tracking platforms such as MLflow or Weights & Biases
  • Knowledge of software engineering best practices including testing, version control, documentation, and code reviews
  • Experience working in collaborative and globally distributed environments

Preferred Qualifications

  • Experience with MLOps architecture and operational ML systems
  • Familiarity with deep learning frameworks such as PyTorch or TensorFlow
  • Experience with Docker, Kubernetes, OpenShift, CI/CD pipelines, and infrastructure automation
  • Knowledge of model monitoring, observability, and operational performance management
  • Experience with cloud platforms and ML services
  • Understanding of relational, NoSQL, and time-series databases
  • Familiarity with LLM, Generative AI, or AI application deployment concepts

Roles and Responsibilities

  • Design, build, deploy, and maintain production-grade machine learning solutions
  • Partner with data scientists to operationalize models and analytics products
  • Build scalable data and feature pipelines
  • Optimize model performance, reliability, and operational efficiency
  • Develop monitoring, alerting, and observability capabilities for ML systems
  • Improve MLOps processes, deployment standards, and engineering practices
  • Contribute to CI/CD and automation initiatives across the ML lifecycle
  • Support model governance, reproducibility, and operational excellence
  • Collaborate with international stakeholders across ING's analytics ecosystem

Generative AI & LLM Engineering Exposure

As ING Analytics continues to expand its AI capabilities, you will also have opportunities to contribute to the operational foundation of Generative AI solutions. This includes:

  • Supporting deployment and lifecycle management of LLM-powered applications
  • Integrating AI services into production banking workflows
  • Building monitoring and evaluation capabilities for Generative AI systems
  • Contributing to responsible and scalable AI adoption within a regulated financial environment

We hire based on potential, not just credentials. You'll be supported from day one through structured onboarding, access to ING's global learning platforms, and a team culture that prioritizes curiosity and continuous growth. Our Istanbul hub is an integral part of ING's global analytics engineering network and your work will help power solutions used across ING's international organization.

Equal Opportunity

Don't meet every single requirement? Don't let that hold you back. Studies show many talented professionals hesitate to apply unless they meet every qualification. If this role excites you and you believe you can make an impact, we'd love to hear from you.

What We Offer at ING Hubs Turkiye

At ING Hubs Turkiye, we believe that your work should be fulfilling in every way. We pay attention to even the smallest details to ensure that your experience is rewarding. Here’s what you can expect when you join our organization:

Be Yourself, Be an ING'er

  • Welcome Leave: Enjoy 14 days of welcome leave, even in your first year. Don’t postpone your dreams.
  • Career Opportunities: We provide self-driven career paths where you can navigate your professional journey.
  • Personal Growth: Engage in challenging work with endless opportunities to achieve your ambitions.
  • Dynamic Environment: Work in an informal, vibrant atmosphere with innovative colleagues supporting your endeavors.
  • Innovation Culture: Share your innovative ideas while exploring PACE methodology with us.
  • Global Exposure: Participate in global projects and expand your career opportunities.
  • Communication & Celebrations: Enjoy various communication activities and celebrations that promote a friendly work environment.
  • Health Care: We offer a comprehensive health insurance package for you and your loved ones, including spouse and children.
  • Private Pension Plan: Secure your future dreams with our private pension plan.
  • Meal Card
  • Transportation Allowance
  • MultiSport Membership
  • English Language Development Support

How to Apply

Click the button on our career site and submit your application through Workday.

About ING

With 65,000 employees and operations in approximately 40 countries, there is no shortage of opportunities for people with initiative who want to help people take a step ahead in life and in business.

Do you want to work at the cutting edge of what’s possible and at the same time ensure you work with integrity and hold the customer’s interests at heart? Do you want to be surrounded by progressive, inspiring, diverse and supportive colleagues?

Then there is no better place to invest your talents than at ING.

Join us. Apply today.

About ING Hubs

Following ING’s strategic ambition to deliver a superior experience to its customers worldwide, the hubs network contributes to fostering efficiency and digitalization across ING. Providing concentrated expertise along with scalable and sustainable solutions, the hubs focus on straight-through processing, delivering automated services like software development, data management and retail operations.

Present in Poland, Romania, Slovakia, the Philippines, Türkiye and Spain, ING Hubs employ more than 13,000 professionals in domains such as software development, data management, operations and non-financial risk.

Discover ING Hubs Türkiye

ING Hubs Türkiye is looking for talents to join an international network of professionals. Building on an existing framework and shared mission, our up-and-coming team will bring its unique personality and skills set to provide borderless services with bank-wide capabilities.

We value strong work ethics, knowledge sharing and flexibility in our way of working – it is both our promise to you and what we look for in new colleagues.

Let's meet!

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Frequently asked questions

What skills are required for Machine Learning Engineer at ING?

The required skills for Machine Learning Engineer at ING include: Python, Spark, Scikit-learn, MLflow, Git, PyTorch, TensorFlow, Docker, Kubernetes, OpenShift, CI/CD, LLM, Generative AI.

What is the seniority level for Machine Learning Engineer at ING?

Machine Learning Engineer at ING is a Senior level position.

How do I apply for Machine Learning Engineer at ING?

You can view the full description and apply for Machine Learning Engineer at ING on EchoJobs: https://echojobs.io/job/ing-machine-learning-engineer-ydfbr.