Data Engineer (MLOps)
Remote - Wrocław, Lower Silesian Voivodeship, Poland
riskmethods- the intelligent way to manage risk!
Engage with our software and help companies proactively protect money and reputation. Bring in your own ideas to improve our product strategy, closely collaborate with partners and internal stakeholders to make our product even more successful and bring it to the next level.
Are you ready to take an opportunity to jump start you career with the next SaaS champion in Supply Chain Risk Management? Then read this carefully! For our Wrocław office, we are looking for an aspiring and motivated team player as our new Data Engineer
What you will do:
- Work in an agile company that develops a successful, AI-based Supply Chain Risk Management application
- Deploy and maintain Machine Learning (ML) REST API services
- Develop data-intensive application that operates in a real-time fashion
- Drive adoption and implementation of DevOps practices in ML context
- Design scalable and maintainable deep learning inference pipelines
- Collaborate with other colleagues to document and maintain ML services
What you should bring along:
- You have 4+ years of experience building data intensive application
- You have experience deploying machine learning models to production
- You are proficient in Python and familiar with packages such as Pandas, TensorFlow and/or Pytorch
- You have a good understanding of the complete lifecycle of ML model development
- You are familiar with the concepts of A/B deployment and model differential testing
- You have experience working with cloud providers (AWS/GCP/Azure)
- You have experience working with structured and unstructured data
- You have a positive, can-do mentality and can communicate to non-experts well
- You have at least a bachelor’s degree in Computer Science, Mathematics, Engineering, or a related discipline
- You have a strong command of English, as it is our primary communication language
- You have experience setting-up CICD pipelines in ML context
- You have experience building machine learning models
- You are interested in Knowledge Graphs
What we offer you:
- An eager, open-minded and international Go Live Team as great work environment!
- Unique learning opportunity working with machine-learning experts, data engineers, software and data architects, product owners, and scrum masters as one Team
- Exciting technologies to work with and to support our growing customer base
- An agile mindset uplifting your personal growth and professional development
- An impact on our company and the business of our customers by bringing in your ideas
- Conferences and trainings to stay up to date with the latest industry updates
- Plenty of fun, team events, drinks and great colleagues
If you want to work in an agile environment (not only by doing Scrum), we are looking forward to your application.
riskmethods provides our customers with a cloud-based supply chain risk management solution. Our innovative AI-driven service empowers businesses around the world to proactively identify, assess and mitigate risk in their supply chains to protect revenue and reputation. At riskmethods, we work cooperatively to ensure our customers’ success. We welcome new perspectives, insights and ideas and believe in our people. We offer a flexible working environment including the opportunity to work remote and support each “riskbuster” in achieving their personal goals and in making a difference. Our company values are to think big, get stuff done, hate waste and act respectfully. We are expanding rapidly and are looking for new “riskbusters” to drive our strong growth trajectory.
By sending an application form to riskmethods, you agree to the processing by the Employer/Data Controller of your personal data contained in the recruitment application in order to carry out the recruitment for the position indicated in the advertisement.
If you are not sure whether you have the right qualifications, we encourage you to talk to us. We are looking forward to receiving your complete application, including your portfolio, potential start date as well as salary expectation. In case you have questions, feel free to get back to us at email@example.com