What you'll do Lead and manage the MLOps team, fostering a collaborative and performance-driven environment.Develop and implement strategies for scalable and efficient machine learning model development and deployment.Oversee the end-to-end machine learning lifecycle, including data preparation, model training, validation, deployment, and monitoring.Collaborate with cross-functional teams (Applied Scientists, Data Scientists, Software Engineers, Product Managers) to integrate ML models into products and services.Ensure adherence to best practices in ML model governance, security, and compliance.Drive continuous improvement in MLOps processes and tools, leveraging the latest advancements in technology.Provide technical guidance and mentorship to team members.Manage the budget, resources, and timelines for MLOps projects.What you'll need Bachelor's or Master's degree in Computer Science, Engineering, or a related field.Minimum of 5 years experience in a similar role, with a focus on machine learning, data science, or software engineering.Proven experience in managing and scaling ML models in production environments.Strong knowledge of ML frameworks and cloud platforms (Azure, AWS).Experience with containerization and orchestration technologies (Docker, Kubernetes).Familiarity with MLOps tools and practices (CI / CD, monitoring, logging).Excellent leadership and team management skills.Strong problem-solving and analytical abilities.Excellent communication and interpersonal skills.Meet your team We're Maps, a global team within TomTom's Location Technology Products technical unit. Our team is driven to deliver the most up-to-date, accurate and detailed maps for hundreds of millions of users around the world.
Joining our team, you'll continuously innovate our mapmaking processes, directly contributing to our vision: engineering the world's most trusted and useful map.
At TomTom... You'll help people find their way in the world. In 2004, TomTom revolutionized how the world moves with the introduction of the first portable navigation device.
Now, we intend to do it again by engineering the first-ever real-time map, the smartest and most useful map on the planet.
Work with a team of 3,700 unique, curious and passionate problem-solvers. Together, we'll open up a world of possibilities for car manufacturers, enterprises and developers to help people understand and get closer to the world around them.
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