R&D Engineer Explainability
With our product Deeploy we try to solve one of the biggest challenges in AI nowadays: making AI/ML truly accountable. Deeploy originated from within Enjins and is now a fast-scaling MLOps company, fully devoted to creating state-of-the-art MLOps software for AI developers. If you want to be part of a fast-growing software engineering team, you like technical challenges and unexplored territory, then you should join us!
You will be directly involved in our product team for the development of our Machine Learning serving platform. Realising innovative features around deployment, monitoring and explainability of Machine Learning.
The Machine Learning services are witten in Python so experience is required. Experience working with other parts of our stack is a bonus, particularly TypeScript, Docker, Kubernetes and PostgreSQL.
Who are you?
- You have a preference for a pragmatic, ambitious, small and close team
- You want to experience a fast paced startup and work on applying breakthrough research in our platform to immediately test it in practice
- You have a solid academic foundation in applied Machine Learning and software engineering
- You have at least 2 years of relevant experience in industry or academia
- You like working on model explainability, drift detection and model monitoring
- You like to review existing academic literature and research software
- You have solid experience with Python, TensorFlow and/or PyTorch
- You are passionate about the world of Machine Learning and AI and believe it is of great importance to apply it in the fairest way possible
What do we have to offer?
- A young and ambitious team with challenging projects and customers
- Focus on personal growth and development
- Celebration of small and big milestones reached together
- A growing amount of responsibility regarding sales and personal growth