Valeo is a global technology company that designs innovative solutions to reinvent mobility. We are an automotive supplier and partner to automakers worldwide, with a vision to invent a greener and more secure mobility through intuitive driving and reduced CO2 emissions.
Our Mission
To deliver market-leading perception solutions for Advanced Driver Assistance Systems (ADAS) and parking functions. Our state-of-the-art, data-driven approach harnesses the expertise of our global community to provide safe, reliable, and innovative perception solutions.
Your Mission:
* Lead the MLOps team globally.
* Develop end-to-end Ops pipelines based on cloud/on-premise platforms, AI lifecycle, and business requirements.
* Take AI from the lab to everyday life on the road for multi-sensor ADAS and Autonomous Driving perception applications.
Your Responsibilities
* Coordinate a global team of software engineers to develop and manage MLOps tools that automate and improve deep learning software development and model building practices.
* Develop and implement MLOps strategies, roadmaps, best practices, and standards to enhance AI ML model deployment and monitoring.
* Oversee the design, deployment, and management of scalable and reliable infrastructure for model training and deployment, both on-premise and on the cloud.
* Create and maintain robust monitoring systems to track model performance, data quality, and infrastructure health.
* Develop and maintain automated pipelines for model training, testing, and deployment, optimizing for speed and reliability.
* Collaborate closely with data scientists, ML engineers, and SW engineers to support smooth integration of ML models into production systems.
* Collaborate with business and PM stakeholders in roadmap planning and implementation efforts.
Requirements
* Degree in Software Engineering or equivalent.
* Minimum 3 years relevant experience in AI/MLOps engineering.
* Strong knowledge of machine learning concepts, algorithms, and tools.
* Experience with data preparation and management tools.
* Expertise with cloud computing platforms such as AWS, GCP, or Azure.
* Excellent analysis & trouble-shooting skills.
* Excellent communication skills, both written and verbal.
* Strong experience in capitalising knowledge & best practices.
* Strong experience in managing, training, and mentoring team members.
* Confident, articulate, self-motivated, determined, and energetic.
* Self-starter, motivated individual who can work fully autonomously.