Machine Learning Platform Engineer

Machine Learning Platform Engineer

The client

As a global financial institution, ING is at the forefront of innovation, continually seeking to leverage data to drive better decision-making and enhance customer experiences. With a strong commitment to becoming increasingly data-driven, ING is dedicated to fostering an environment where cutting-edge technologies are embraced to transform insights into actionable strategies.

 

The department: Analytics Engineering

Join the Analytics Engineering team, a dynamic group of over 50 professionals (and growing rapidly) committed to propelling ING towards a data-driven future. Our mission is to merge Big Data technology with Data Science, crafting high-value solutions and products. We cultivate a stimulating and collaborative atmosphere where creativity flourishes, and each member is empowered to excel both individually and collectively.

 

The squad

Join our team of seven engineers (including ML Platform Engineers and MLOps Engineers) as we embark on the creation of a cloud-ready Data Analytics Platform. This collaborative effort spans across various ING units, offering the opportunity to work in a distributed, multi-national, and multi-cultural environment. Expect plenty of exciting challenges and rewarding experiences as we collectively strive to push the boundaries of innovation.

Job description

Are you passionate about pioneering work in Machine Learning Engineering? As a Machine Learning Platform Engineer within the Analytics Engineering team, you'll embark on a journey to support various projects by assisting data scientists in training, deploying, monitoring, and operationalizing models. Your primary responsibility will involve developing and maintaining a robust data execution platform, advocating for best coding practices, and producing reusable code.

 

Responsibilities

· Collaborate with data scientists to facilitate the development and deployment of machine learning models.
· Build and maintain a scalable and efficient data execution platform.
· Ensure adherence to software engineering practices such as versioning, testing, documentation, and code review.
· Utilize your expertise in technologies and frameworks like sklearn, MLFlow, TensorFlow, and Apache Airflow.
· Develop and maintain SQL and noSQL databases, ensuring optimal performance and reliability.
· Implement monitoring and observability solutions to ensure model performance and system health.
· Drive automation efforts for deployment and provisioning using tools like Docker, Openshift, and CI/CD pipelines.
· Contribute to the advancement of advanced analytics, data science, and NLP capabilities within the organization.

Ideal candidate characteristic
· Experience with ML technologies such as sklearn, MLFlow, and TensorFlow. 
· Proficiency in SQL and noSQL databases, including data manipulation and transformation. 
· Familiarity with infrastructure tools like Apache Airflow, MFlow, Kubernetes, Docker, Openshift, and CI/CD pipelines.
· Experience with monitoring tools for system health.
· Additional skills in Advanced Analytics, Data Science, and NLP.

 

Nice to have
· Hands-on experience with big data technologies like S3, Spark, Kafka, and Flink.
· Knowledge of system design principles.
· Skills in Bash scripting, Linux systems administration.
· Proficiency in statically typed languages like Scala, Java, or Go.
· Familiarity with cloud environments, especially GCP.
· Understanding of various databases, including RDBMS, non-SQL, and time-series.
· Experience in agile/scrum methodologies.
· Contribution to Open Source projects is a strong plus.

What we offer
· initial 8-month-assigment with extension possibility
· 40 hour work week
· hybrid working
· transit and/or working from home allowance
· internet allowance
· € 5.996,00 - € 8.700,00 gross per month (depending on experience)
· holiday payment (8,33% on your gross annual income)
· 25 paid holiday days (based on 40-hour week)
· 13th salary
· full pension contribution