IT Platform Engineer for MLOps (Machine Learning) Area

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In Data Science Platform Squad, we Build and maintain a generic, scalable and govern platform for Data Science model of online models to enable an automated, compliant and efficient Model Life Cycle process. We use technologies like Open-Shift to build Containerized platform for Hosting Model execution & Deployment.

Our squad is responsible for hosting Python statistical and machine learning models, primarily serving the Data Science communities who develop these models on behalf of various enterprise domains within the bank. We manage AAPF (Advanced Analytical Platform for Fraud), which works alongside CMDEP (Containerized Management Deployment and Execution platform) to execute machine learning models for scoring payment transactions for fraud, including e-banking domestic/international and District International models deployed in CMDEP. Additionally, we are tasked with transforming the current On-Prem infrastructure into a Cloud-Native platform.

As a MLOps IT Platform Engineer, you will work closely with the Product Owner and Chapter Lead in a “2 in a box” model, using agile methodologies. You will be responsible to develop and maintain scalable ML pipelines on futured MLOps platform built on AWS and Databricks. You will be tasked with ensuring seamless and automated transition of models from development to production using CICD workflows, implement the infrastructure as code. You will ensure that our machine learning models operate reliably, efficiently and at scale.

You will:

Implement automated pipelines for model training, validation and inference
Build and maintain CI/CD workflows using Github actions to ensure model code is versioned and seamlessly deployed to production
Utilize tools like MLflow for model tracking, versioning and deployment
Use terraform to provision and manage scalable secure infrastructure required for ML workloads
Leverage docker containers to build, deploy and manage containerized ML models

About you:

Minimum of 2 years of practical experience in MLOps platform to build model development deployment, execution and maintenance of ML pipelines
In-depth knowledge of AWS services and Databricks
Proficiency in Python, Pyspark
Experience in CI/CD tools Terraform and container orchestration
Problem-solving and debugging skills
Understanding and practical experience with PubSub and Kafka streaming services would be beneficial
Upper-Intermediate English skills

We offer:

Monthly salary range from 3280 EUR to 4920 EUR gross (based on your competencies relevant for the job).

Additionally, each Danske Bank employee receives employee benefits package which includes:

Growth opportunities: professional & supportive team, e-learnings, numerous development programs; (incl. professional certificates); 100+ professions for internal mobility opportunities.
Health & Well-being: a diverse, inclusive, work & life balance work environment; additional health insurance; mental well-being practices; partial psychologist counselling compensation; silence and sleep zones at the office; game rooms.
Hybrid working conditions: Work from home up to two days a week; home office budget (after the probation period); modern Danske Campus workplace developed with anthropologist for the best employee experience.
Additional days of leave: for rest, health, volunteering, exams in higher education institutions, and other important activities. Moreover, for seniority with Danske Bank.
Monetary compensation package: accidents & critical diseases insurance; financial support in case of unfortunate events, travel insurance; IIIrd Pillar Pension Fund contribution.