Full Stack Data Engineer
Medewerker | Informatie Technologie | Ervaren | Amsterdam | 2020-02-13 | REQ-10025539
ING is regularly looking for Full Stack Data Engineers. Are you interested to be included in the candidate pool of our future positions in this area? Please see the role description below and apply. We will contact you once the vacancy is open.
Think Forward! Our purpose is to empower people to stay a step ahead in life and in business. We are an industry recognized strong brand with positive recognition from customers in many countries, a strong financial position, omni-channel distribution strategy and an international network. If you want to work at a place where we believe that you can live by the Agile manifesto without jeopardizing the necessary continuity, compliance and QA measures, where we are committed to delivering stable and secure services to end users, and where we have a 'no nonsense' getting-things done mentality, please read on!
As an Full Stack Data Engineer you will be joining ING’s Advanced Analytics global organization and will partner with Data Scientists in our centre of expertise to research, design and implement leading-edge algorithmic products. We are looking for a passionate, Senior-level, Software Engineer with a strong background in machine/deep learning and experience building Machine Learning pipelines to help us operationalise/productionalise world class ML models at scale.
You will be part of the technology team, taking care of software engineering challenges associated with data science and machine learning. You will be serving and deploying models and putting research into production. Through collaboration with architects, data engineers and data scientists, you will write code that applies AI technology to optimize the development and put them into production including post deployment production. Leveraging your knowledge and experience of back-end programming languages and architecture, you will also write the scalable and performant microservices that host the algorithms in both on-premise and cloud environments.
You will be responsible for:
- Analytics software development
- Building production level ML/AI solutions, with solid software engineering and ML/AI principles
- Build tools to enable fast, reproducible, and organized experimentation by model developers
- Working closely with data scientists to put their developments into production. This means parallelizing, optimizing, tuning, testing and wrapping code that exists as a proof of concept into something that can be deployed
- Model Ops
- Automated deployment, and monitoring
- Always thinking a step ahead and never satisfied with the status quo
- Enthusiasm for helping others to be successful and a drive for taking it on and making it happen
- You have a learning attitude. Not only to master new technologies and programming languages, but also on the interpersonal level. You are proven to be able to ask and give feedback
- You embrace challenges in a fast changing and complex environment
- You are a naturally collaborative person who listens and invests in others to achieve common goals
- You have a Pro-active and can-do attitude (self-steering)
ING Analytics is an organisation responsible for realizing this vision for ING, differentiating ING as a leader in data-driven organizations within the banking sector and beyond. The organisation consists of a number of Global Analytics Centre of Excellences around the bank’s key capabilities (such as Pricing, Risk Management, Financial Crime & RegTech, Customer Intelligence, etc.) as well as strong coordination areas around people capabilities, technology, data, tooling, and external partnerships.
The Data, Tools & Technology team is one of the five core teams within ING Analytics Unit. It is responsible for driving overall strategy and roadmap for analytics platforms, technology and tooling, industrialisation of analytics models and data roadmap for all the work streams, change management activities and their interdependencies.
Do you recognize yourself in this profile?
- At least Master Degree in Software Engineering / AI / Computer Science
- Can build an “end-to-end software product” which has machine learning components
- Strong skills in Python/R, Java and Scala, and reasonable SQL understanding
- A minimum of 5 years' experience in building ML/deep learning pipelines and models
- Experience in implementing production ready ML models using current ML/Deep learning techniques
- Experience with Deep learning frameworks like Tensorflow, PyTorch etc. and other Big data technologies like Hadoop/Hive, PySpark, SparkR, etc.
- Experience writing RESTful web services
- Experience with industry-accepted testing tools and frameworks such as Selenium, TestNG, JUnit, and/or Cucumber
- Experience with DevOps technology (such as Jenkins and Docker)
- Experience with enterprise source code management (GitHub, RTC, etc.)
- Experience with CI/CD for Machine Learning pipeline (CD4ML)
Nice to have:
- PhD in Software Engineering / AI / Machine Learning / Natural Language Processing
- Experience with one or more of the following: Natural Language Processing, text understanding, classification, pattern recognition, recommendation systems, unsupervised learning, ranking systems or similar
- Experience with Test Driven Development
- Good knowledge of open source technology such as Apache ecosystem
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 hour week)
- Great training and education opportunities
Are you keen to know more or apply
If this is the sort of environment you thrive in, then apply and join us in changing the future of banking!
We look forward to getting to know you!