INGMachine Learning DevOps Engineer
ING is hiring a Machine Learning DevOps Engineer. Level rates it ; you can apply on Level.
AI in this role
Build and maintain machine learning infrastructure and fraud detection models within a distributed computing environment.
ING Hubs Poland is hiring!
The expected salary for:
expert position: 13 000 - 28 000 PLN
The financial ranges specified in the announcement are adjusted and may differ from the range specified in the remuneration regulations.
We are a dynamic and rapidly growing tech company, seeking a talented Machine Learning DevOps Engineer to join our team. The successful candidate will be responsible for developing platform and implementing fraud detection models within the banking sector.
We are looking for you if:
- You have experience with cloud platforms: GCP, Azure (DevOps).
- You have experience with GitHub, Airflow/Cloud Composer, Spark/DataProc, Terraform, containerization.
- You are proficient in data & software engineering with a special focus on distributed computing (Spark 3.5+).
- You are familiar with 'Clean Coding' paradigms and have programming experience in Python.
- You understand ML Ops and have been involved in ML model deployment.
- You are familiar with model development frameworks (Scikit-learn, Pandas, NumPy).
- You possess excellent problem-solving skills, attention to detail, and the ability to work both independently and collaboratively.
- You have excellent communication and teamwork skills.
You'll get extra points for:
- Hands-on experience with code/compute optimization and tuning testing.
- Proven capability in handling large data sets for developing fraud detection models.
- Master's degree in computer science, statistics, data science or a related field.
- Experience with other machine learning frameworks and libraries.
- Certifications in relevant fields.
- Experience in the banking sector, particularly with fraud detection systems.
Your responsibilities:
- Code/compute optimizations & (unit) testing.
- Scheduling & distributing code on our data analytics platform.
- Working with shared model development codebase.
- Assist in model development/deployment.
- Collaboration with data scientists in squad.
- Maintenance.
English level: B2
Information about the squad:
Are you interested in becoming an integral part of a pioneering team that cooperates in designing, building, and implementing models in the realm of banking fraud detection? We employ a wide range of technologies. Our team enjoys the flexibility to experiment with cutting-edge technologies and techniques in the field of machine learning.
Our clientele includes various divisions of the ING Group, spanning countries such as the Netherlands, Germany, Spain, Italy, Poland, and Romania. By joining us, you will have the opportunity to implement and optimize machine learning models on a global scale, crafting innovative solutions for customers in diverse countries. We are committed to continuous professional development and offer every team member the chance to expand their skills and pursue their interests in a dynamic and collaborative environment.
Our team operates within a Scrum framework, and we're currently seeking an additional ML DevOps Engineer who will enrich our team.
The role naming convention in the global ING job architecture will be “Engineer IV”
How we rate this
Machine Learning DevOps Engineer at ING rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● 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.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you monitor a model once it's live, and how do you know it needs retraining?
- Tell me about a project where mlops was part of your work. What did you do?
- Tell me about a project where distributed computing was part of your work. What did you do?
- Tell me about a project where fraud detection was part of your work. What did you do?
- Tell me about a project where machine learning was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: ML Ops, MLOps, Distributed Computing, Fraud Detection, and Machine learning. 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.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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