MLOps Team Leader

At UVeye, we're on a mission to redefine vehicle safety and reliability globally. Founded in 2016, we have pioneered the world's first fully automated suite of vehicle inspection systems. At the heart of this innovation lies our advanced AI-driven technology, which represents the pinnacle of machine learning, GenAI, and computer vision within the automotive sector.

With close to $400M in funding and strategic partnerships with industry giants such as Amazon, General Motors, Volvo, and CarMax, UVeye stands at the forefront of automotive technological advancement. Our growing global team of over 200 employees is committed to creating a workplace that celebrates diversity and encourages teamwork. Our drive for innovation and pursuit of excellence are deeply embedded in our vibrant company culture, ensuring that each individual's efforts are recognized and valued as we unite to build a safer automotive world.

We seek an experienced technical leader to head our MLOps team.

In this role, you will lead a team of developers and build and maintain our machine learning infrastructure and deployment pipelines. This role combines technical expertise in machine learning operations with strong leadership abilities to guide our team of engineers in delivering scalable ML solutions.

A day in the life and how you’ll make an impact:

• Build, recruit, and lead a team of MLOps engineers.
• Architect and implement enterprise-scale MLOps infrastructure
• Code ML Infrastructure & Framework for Agile ML Lifecycle, MLOps, and CI/CD.
• Design and optimize model-serving architectures
• Ensure high availability and scalability of ML systems
• Collaborate with Algorithm Engineers to deliver innovative solutions.
• Partner with product teams to align ML solutions with business objectives
• Communicate technical plans and progress to stakeholders
• Establish and enforce MLOps standards and best practices
  
  

• BSc in Computer Science or industry equivalent.
• Backend engineer with at least 7 years of experience
• Proficiency in Python and common ML frameworks.
• Proven track record of leading technical teams
• Excellent communication and interpersonal skills
• Strong background in software engineering
• Experience with cloud platforms (AWS/GCP)
  
  

• Experience with MLOps platforms (MLFlow, Kubeflow)
• Experience with optimizing algorithm implementations
• Experience with GPU/CPU optimizations