Senior MLOps Engineer STP

The Team

Within ING, there is ING Analytics (INGA) - a major driving force in its digital transformation of the bank. 

By creating measurable value for ING and its customers through world-class analytics products and services, INGA helps ING to become a leader in data-driven decision-making. Among others, INGA delivers call & speech analytics, generative AI in risk summarization, insights into portfolio performance, advanced ESG data insights (commercial purposes), data analytics platforms (cloud and on-premises), and many more.

A working day in the life of a Machine Learning Engineer

A typical day for a machine learning engineer starts with coffee, catching up with colleagues, and drafting a plan for the coming day. After the standup, you may start analyzing algorithms to identify which of them works well with the problem you are trying to solve. For the rest of the morning, you could experiment in Jupyter notebook using Scikit Learn oruse IDE to continue developing a class that implements a model or interfaces with the database.

After lunch, meet with the team to discuss the next iteration of the product, or go over new features that need to be implemented and discuss how to create or calculate those features. Wrap up the day working on the monitoring tool for machine learning models.

How to succeed

Minimum Qualifications

• Bachelor's degree or equivalent practical experience.

• Excellent communication skills, capable of working collaboratively in a semi-remote, globally distributed team. 

• Hands-on experience building complex data pipelines (e.g., in Apache Spark).

• Hands-on experience with technologies and frameworks used in ML (e.g., sklearn, MLFlow, etc.)

• Knowledge of software engineering best practices (versioning, testing, documentation, etc.)

• A minimum of 5 years work experience

Preferred Qualifications

• Curious mindset; you are collaborative and passionate about helping others to grow and improve.

• Knowledge of MLOps architecture and practices.

• Experience with monitoring and observability.

• Experience with deployment and provisioning automation tools and concepts, e.g., Docker, Openshift, CI/CD.

• Good understanding of different data storages (e.g., RDBMS, non-SQL, and time-series databases).

Rewards and benefits

We want to make sure that it’s possible for you to strike the right balance between your career and your private life. You can find out more about our employment conditions at Benefits in the Netherlands

The benefits of working with us at ING include:

• A salary tailored to your qualities and experience

• 24-27 vacation days depending on contract

• Pension scheme

• 13th month salary

• Individual Savings Contribution (BIS), 3.5% of your gross annual salary

• 8% Holiday payment

• Hybrid working to blend home working for focus and office working for collaboration and co-creation

• Personal growth and challenging work with endless possibilities

• An informal working environment with innovative colleagues

About us

With 60,000 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 business. Do you want to work at the cutting edge of what’s possible while ensuring 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!