ML Ops Manager

7 months ago

Tuam, Ireland Valeo Full time

Valeo is a tech global company, designing breakthrough solutions to reinvent the mobility. We are an automotive supplier partner to automakers and new mobility actors worldwide. Our vision? Invent a greener and more secured mobility, thanks to solutions focusing on intuitive driving and reducing CO2 emissions. We are leader on our businesses, and recognized as one of the largest global innovative companies.

Our Mission:

Valeo is an automotive supplier and partner to automakers worldwide. As a technology  company, we design innovative solutions for smart mobility, with a particular focus on  safer driving and reducing CO2 emissions.

Our mission is to deliver market-leading perception solutions for ADAS driving and parking functions. Through our state-of-the-art, data-driven approach, we harness the expertise of Valeo's global community to provide safe, reliable, and innovative perception solutions. 

We aim to develop and deliver a modular, scalable, and hardware-agnostic full perception stack, utilising Valeo's technology leadership in sensing and ADAS computing platforms.
 

Your Mission:

  • Lead the MLOps team globally.

  • Develop end-to-end (Data/Dev/ML) Ops pipelines based on in-depth understanding of cloud/on-premise platforms, AI lifecycle, and business requirements.

  • Take AI out of the lab and into everyday life on the road for multi-sensor ADAS and Autonomous Driving perception applications.

Your Responsibilities:

  • Co-ordinate a dedicated global team of software engineers to develop and manage MLOps tools that help automate and improve our deep learning software development and model building practices.

  • MLOps Strategy: Develop and implement MLOps strategies, roadmaps, best practices, and standards to enhance AI ML model deployment and monitoring.

  • Infrastructure Management: Oversee the design, deployment, and management of scalable and reliable infrastructure for model training and deployment, both on-premise and on the cloud.

  • Monitoring and Optimization: Create and maintain robust monitoring systems to track model performance, data quality, and infrastructure health.

  • Automation: Develop and maintain automated pipelines for model training, testing, and deployment, optimizing for speed and reliability. Ensure CI-CD best practices.

  • Internal Collaboration: Collaborate closely with data scientists, ML engineers, and SW engineers to support smooth integration of ML models into production systems.

  • Stakeholder Engagement and Collaboration: Collaborate closely with business and PM stakeholders in roadmap planning and implementation efforts and ensure technical milestones align with business requirements.

Education/Training:

  • Degree in Software Engineering or equivalent.

  • Minimum of 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 using a structured documented approach.

  • Excellent communication skills, both written and verbal.

  • Strong experience in capitalising knowledge & best practices through creation and/or updating of standards.

  • Strong experience in managing, training and mentoring team members.

  • Confident, articulate, self-motivated, determined & energetic.

  • Self-starter, motivated individual who can work fully autonomously.