Machine Learning Software Engineer [rekrutacja online]

• Strong skills in Python and Java, and reasonable SQL understanding
• 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 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)

• PhD in 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.
• Experience in R programming.

• Can build an “end-to-end software product” which has machine learning component
• 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 industry-accepted testing tools and frameworks such as Selenium, TestNG, JUnit, and/or Cucumber
• At least Master Degree in AI / Machine Learning / Software Engineering / Computer Science
• Learning attitude. Not only to master new technologies and programming languages, but also on the interpersonal level. Proven to be able to ask and give feedback
• Naturally collaborative person who listens and invests in others to achieve common goals
• Pro-active and can-do attitude (self-steering)

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. The team builds and manages a cutting-edge Machine Learning Platform called ML Platform which is ING's Model-as-a-Service Platform Joining us, you will be part of the technology team, taking care of the software engineering challenges associated with data science and machine learning. You will be serving and deploying models, putting research into production. Through collaboration with architects, data engineers, and data scientists, you’ll 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.