Senior Cloud Infrastructure Engineer
hace 2 días
As a Senior Cloud Infrastructure Engineer at Tomtom International Bv, you will be responsible for designing, implementing, and maintaining cloud-based infrastructure that enables massive data storage and processing for various Machine Learning (ML) model types.
Key Responsibilities:- Collaborate with a global team of engineers to ensure the infrastructure is scalable, highly available, and resilient, meeting the demands of real-time data processing.
- Design and implement technical solutions that address complex challenges, particularly in data processing and infrastructure globally across the company.
- Play a pivotal role in integrating Machine Learning Operations (MLOps) tools and frameworks where necessary, working with technologies like Kubernetes, Azure, and Databricks.
- Own the end-to-end development lifecycle, from gathering requirements to deploying solutions, with a focus on building efficient and maintainable infrastructure.
- Lead design decisions, contribute to architectural discussions, and take ownership of major projects or project steps, ensuring high-quality solutions are delivered.
- Troubleshoot and resolve complex technical issues, leveraging your deep understanding of infrastructure design and cloud technologies.
- A Bachelor's degree in Computer Science (or related field) or 4+ years of relevant industry experience in infrastructure development.
- Expertise in building and managing data processing systems with cloud technologies such as Azure, Kubernetes, and Databricks.
- Proficiency in at least one modern programming language, such as Python or Scala, and experience with scalable system design.
- Solid understanding of professional software engineering best practices—code reviews, source control, testing, and deployment processes.
- Ability to work independently, taking ownership of projects and delivering high-quality, maintainable solutions.
- Excellent communication skills, both written and verbal, in English, to collaborate effectively with a distributed team.
- Experience in Machine Learning, algorithms, and Computer Vision technologies.
- Strong familiarity with MLOps principles and tools, including CI/CD pipelines, observability, and infrastructure as code (IaC).
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