ML DevOps Engineer
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ML DevOps Engineer
On behalf of a leading software company, we are looking for agile DevOps engineer well-versed in ML data preparation and model management. The position is a full-time position.
You will take a role in a newly assembled product development team, but we can unfortunately not reveal the specific details of your mission before you have signed an NDA. In the role, you will design the data pipelines and engineering infrastructure to support the clients’ enterprise machine learning systems at scale and, furthermore, identify and evaluate new technologies to improve performance, maintainability, and reliability of the clients’ machine learning systems.
Moreover, your tasks will be to:
- Take offline models data scientists build and turn them into a real machine learning production system
- Develop and deploy scalable tools and services for clients to handle machine learning training and inference
- Apply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.
- Support model development, with an emphasis on auditability, versioning, and data security
- Facilitate the development and deployment of proof-of-concept machine learning systems
- Communicate with clients to build requirements and track progress
- Support definition of platform architecture and tech stack
- Analyze and test technology components
- Partner with research on new solutions and technologies
- Use agile/lean/startup principals in way of working
- Contribute to Product Development activities across full life cycle
To succeed, in the collaborative company culture you need to have a humble approach towards tasks and new learning. As such, you are known for your open-minded and flexible approach and your ability to handle all tasks with the same dedication. Furthermore, we believe that you have;
- Experience building end-to-end systems as a Platform Engineer, ML DevOps Engineer, or Data Engineer (or equivalent)
- Experience with platform operations
- Strong software engineering skills in complex, multi-language systems
- Fluency in Python
- Comfort with Linux administration
- Experience working with cloud computing and database systems
- Experience building custom integrations between cloud-based systems using APIs
- Experience developing and maintaining ML systems built with open source tools
- Experience developing with containers and Kubernetes in cloud computing environments
- Familiarity with one or more data-oriented workflow orchestration frameworks (KubeFlow, Airflow, Argo, etc.)
- Ability to translate business needs to technical requirements
- Strong understanding of software testing, benchmarking, and continuous integration
- Exposure to machine learning methodology and best practices
- Exposure to deep learning approaches and modelling frameworks and notebooks (PyTorch, Tensorflow, Jupyter, etc.)
- Experience with video products is preferred
- Fluent with Agile / Lean methodologies
- Proficient in using Kanban boards to track tasks, assignments, etc.
The position is a full-time position. It will be possible to start the 1st of September. Your new workplace will be the headquarters located in the outskirts of Copenhagen. Nevertheless, the company offers flexible working conditions.