Chapter Lead Machine Learning Platform
ING is looking for an experienced Machine Learning Platform Engineer to help build on our Global Analytics ambition
As a chapter lead of Machine Learning Platform Engineering, you will be joining ING’s Advanced Analytics global organization. You will be leading a chapter of engineers who share core competencies, thereby creating opportunities for your chapter members to reach their full potential and encourage team development. You create a culture in which employees take responsibility, help each other be successful and remain a step ahead. You manage the performance review process for your chapter colleagues.
You work part-time as a Platform Engineer: be a regular squad member and continue to apply your Software Engineering expertise and domain experience in productionalizing machine learning models. You positively contribute to putting research into production, the vision in your area, and introduce & nurture innovation within it.
Additionally, you discuss the chapter's resource planning and development needs with the global head of analytics product engineering, encourage knowledge sharing, and apply engineering best practices to analytics applications.
Machine Learning Platform
Before a machine learning model can add value to an organization, it needs to run in Production. Getting a model to production is notoriously challenging. You need to account for IT, compliancy, monitoring, integrating with other applications, etc. Going through this process for every model is both time-consuming and expensive. For this reason, we have developed the Machine Learning Platform, to empower engineers and data scientists across ING to easily deploy and run Machine Learning Models in production, safely, compliant and at scale. You will be responsible for this platform, its roadmap, and positioning it within ING.
You work with your peers to overcome challenges and, collectively, do a better job.
You cocreate the analytics engineering area vision, set the long term technical roadmap.
Manage, coordinate and deliver enterprise level projects.
You are the hierarchical lead of your chapter and responsible for effectively managing squad resources.
Together with Analytics Product Owners and Chapter Leads, you help others to be more successful by focusing on craftsmanship, improving and sharing the Way of Working, and creating a high performing team.
You are the lead for performance management, training plans, and daily people management for your chapter.
You lead the chapter meet-up and ensure way of work-related information is shared and craftsmanship improved.
You work closely with data scientists, architect and backend engineers to productionalize machine learning use cases on the platform.
Follow and improve coding and security standards to build a robust, reliable and compliant platform.
Stay on top of new trends in machine learning engineering and MLOps technologies.
Extensive experience with systems engineering in a highly regulated enterprise environment.
Extensive experience in building 0-downtime distributed software systems.
Extensive experience in Functional Programming, preferably Scala.
Experience with Java and Python.
Experience with productionalizing Machine Learning Models and the model life cycle.
Experience securely building container images (e.g. Docker), running container workloads in production (e.g. Kubernetes).
Experience with source code management (e.g. git).
Experience with building CI/CD pipelines for Machine Learning (CD4ML).
Experience with Azure DevOps or GCP/GKE.
Experience with configuration management technology (e.g. Ansible).
Good understanding of streaming technologies Kafka or Flink.
Good understanding of databases; both RDBMS and non-SQL (preferably Cassandra).
Being an Open Source contributor is a strong plus.
Master Degree in AI / Machine Learning / Software Engineering / Computer Science or related field.
Always thinking a step ahead and never satisfied with the status quo.
Enthusiasm for helping others to be successful and a talent for taking it on and making it happen.
You have an end-to-end ownership mindset.
You are a naturally collaborative person who listens and invests in others to achieve common goals.
You have the mentality of continuous improvement.
You reflect upon behaviors and performance to proactively identify improvement areas.
You are a strong problem solver to structure and improve complex situations.
You coach others to help their individual development.
A natural communicator with excellent written and verbal skills.
You take pride in your code and take responsibility for keeping it running in production.
What do we offer?
Working at ING means working in a dynamic and international setting. Individual development of our employees is very important and that is why ING offers excellent courses and programs. We only hire people with exceptional talents and capabilities! You will work on the most innovative projects within ING. In addition, we offer:
A competitive salary
Working with highly skilled people
Working in an area which is of great importance to the strategy of ING
A relaxed and fun team
An International atmosphere
A full time position (40 hours per week)
Great training and education opportunities
With around 52,000 employees and operations in approximately 40 countries, there is no shortage of opportunities for people with initiative who want to make a diﬀerence. We hire smart people like you for your potential, not your past. Our biggest expectation is that you’ll stay curious. Keep learning. Take on more responsibility. In return, we’ll back you to develop into an even more awesome version of yourself.
If you want to work at the cutting edge of what’s possible, surrounded by progressive, inspiring and supportive colleagues, there is no better place to invest your talents than at ING. Join us!
Are you keen to know more or apply
If this is the sort of environment you thrive in, then click on apply.
You can express your interest through a letter of application in which you state why you are ideally suited for this position. We would also like to receive your current CV.
We look forward to getting to know you!
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