Machine Learning Engineer Intern

ING is hiring a Machine Learning Engineer Intern for a remote role open to applicants in Italy. Level rates it ; you can apply on Level.

AI in this role

Machine learning intern to build, train, deploy, and monitor predictive models and data pipelines.

scikit-learnpythongitazure

machine-learningdata-analysisci-cddevops

Job Description:

The team applies advanced analytics—including machine learning, quantitative algorithms, and data mining techniques— to obtain business insights and solve problems. We are actively involved throughout the entire lifecycle, from initial design to final implementation. Our stakeholders span all areas of the bank, including business, risk, retail, and corporate banking.

Our scope of work includes:

· Building and maintaining a robust codebase that supports the creation of ML models

· Training, deploying, and monitoring machine learning models tailored to various business needs.

· Conducting ad hoc data analyses

· Developing dashboards and tools to enhance data accessibility and support a more data-driven organization.

The employee will focus on developing an interactive dashboard for computing the profitability and risk assigned of a finance product.

For this purpose, we are looking for students interested in writing their thesis on this topic.

Experiences:

Practical experience (at least 2+ years) with programming language such as Python

Knowledge of Object-Oriented Programming and Git workflows
Experience with CI/CD pipelines and DevOps practices

Skills:

Demonstrated solid data handling skills.
Fluent written and spoken English
Strong verbal and written communication skills

Nice to Have:

Personal public projects on GitHub/Azure or similar
Familiarity with machine learning libraries and frameworks (e.g. scikit-learn...)
Experience in at least one of the following:
- Credit Decision Models
- Business Models (e.g., Churn, Propensity)
- Clustering techniques

Personal Characteristics:

Self-driven with the ability to figure out solutions by him or herself
Ability to work collaboratively in a team environment.
Must possess an energetic, self-motivated work ethic.
Effectively communicate with many levels.
Proven to perform under pressure.
High ethical standards, honesty, integrity.

Location: Milan (hybrid)

Compensation: 1500€/month

How we rate this

Machine Learning Engineer Intern at ING rates 70 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Key facts

Machine Learning Engineer Intern is an open job at ING.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in MILAN and is marked remote.
The job was posted on September 28, 2026.
Seniority: intern.
Applications are handled by ING. Apply on ING

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Machine learningData AnalysisCi CdDevopsscikit-learnPythonGitAzure

Also common in machine learning engineer jobs at this level

AWS

Pay

Typical machine learning engineer job: $197k

Use the typical machine learning engineer figure as a reference when pay comes up. See machine learning engineer jobs

Questions you could be asked

Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where data analysis was part of your work. What did you do?
Tell me about a project where ci cd was part of your work. What did you do?
Tell me about a project where devops was part of your work. What did you do?
Walk me through how you've used scikit-learn in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Machine learning, Data Analysis, Ci Cd, Devops, and scikit-learn. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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