Data Talent Programme - Machine Learning Engineer (f/m)

At a glance

As a machine learning engineer trainee you will learn how to take responsibility on taking models that data scientists develop into production. You will integrate the models with the dedicated platform/application — and that could involve design and build, say, an API around this model so that it can be served and consumed, and then being able to maintain the integrity and quality of this model so that it continues to serve really accurate predictions. As machine learning engineer you may also be responsible of retraining the models already in production. With this Talent Programme you will take the first step in your career as a machine learning engineer to develop yourself personally and professionally!

Your job

• Collaborate with data and Machine Learning engineers to develop and maintain data and model pipelines;
• Apply machine learning and data science techniques and design distributed systems;
• Write production-level code and bring model solutions to production;
• Engage in code and model reviews;
• Produce project outcomes and isolate issues;
• Implement machine learning algorithms and libraries;
• Research and implement best practices to enhance existing machine learning infrastructure;
• Support the entire Machine Learning lifecycle (exploration, development. deployment, monitoring, and maintenance).

Your profile

As a machine learning engineer you should have a Master’s or Ph.D. in computer science, mathematics, or statistics.

Who are you?

• Entrepreneurial spirit, creative mindset and capable of assessing and evaluating risks;
• Knowledge of or at least interested in technology and how this supports business improvements;
• Thrives in an international context;
• Thinks in terms of what’s possible, sees opportunities and takes a solutions-oriented approach;
• Self-starter who readily assumes responsibility;
• You have a valid EU work permit.

What’s your experience?

You must have:

• A firm understanding of machine learning (including the role of algorithm theory in machine learning and complex algorithms that are needed to help machines learn and communicate);
• Strong analytical skills;
• Advanced knowledge of software engineering;
• Experience working with Python and Jupyter notebooks;
• Experience with modern machine learning algorithms;
• A good understanding of both probability and statistics;
• Experience working with large amounts of data in a high throughput environment;
• SysAdmin skills;
• Cloud skills, preferably Azure;
• No more than 3 years of work experience (internships do not count as work experience), this is a graduate programme.

Nice to have:

• Experience working with distributed systems tools like Etcd, Doozer, ZooKeeper
• Experience working with Databricks and/or MLflow;
• Experience working with Docker and/or Kubernetes;
• Extensive knowledge of machine learning evaluation metrics and best practices;
• Competency with infrastructure as code;
• Familiarity with the Agile methodology.

What we offer

In our Data Talent Programme we train you to be the Data Expert who matters now, tomorrow and the day after tomorrow. In this programme you will receive training focused on professional and personal development. We will also continue to invest in you for the longer term and guide you on your journey within the bank. It will be a continuous "experience", in which you work together with the best people and best parties from the market, and you do your work with the latest technologies on the most modern cloud infrastructure.

What does the Data Talent Programme look like?

The ABN AMRO Data Talent Programme offers you a substantively challenging position in which you combine your work with education and training for 18 months. In the first six weeks you will start with a data bootcamp, where you will work on your hard and soft skills with your fellow trainees. Immediately afterwards, you will start at your department in a fixed position where you will work on your own activities and assignments, with the help of your manager and colleagues. Next to your work, you also participate in the personal development programme Boost Your Growth.

Please note this is not a traineeship with different rotations throughout the organisation.

Where will you start in the organisation?

For this role, you will start in one of the departments within our organization. You will do different assignments within your team and after the programme, start as a Machine Learning Engineer for your team. Wherever you end up: a lot has to be done. By joining our Data Talent Programme, you’ll be taking the first step in your personal and professional development towards becoming a data expert.

Interested? Read this carefully

Are you interested? Apply via the button above and upload your resume and cover letter. Do not apply for more than one position within the Data Talent Programme, so choose between the Data Analyst, Data Scientist or Machine Learning Engineer position. We are looking for graduates  with a strong motivation to work for ABN AMRO. The Data Talent Programme starts in the beginning of August 2021. 

Selection process

After you apply you will receive an e-mail within 10 working days to let you know if you have been selected and can move forward to the next round. The overall recruitment process includes:
1.    Apply online with your CV and cover letter;
2.    CV screening by recruitment;
3.    Online capacity test;
4.    CV screening by hiring manager;
5.    Online interview and case presentation by candidate;
6.    Second interview;
7.    Job offer.

If you have any questions, please feel free to contact us at [email protected].

Equal opportunities for all

The success of our organisation depends on the quality of our people and the ideas that they have. Truly surprising insights and innovative solutions for our clients result from an interplay of cultures, knowledge and experience. Diversity is therefore extremely important to our organisation. To ensure that everyone at ABN AMRO can develop their talents, we encourage an inclusive culture in which all colleagues feel engaged and appreciated.