MLOps Manager

Overview

Inchcape is the leading global automotive distributor operating in more than 40 markets. We partner with some of the biggest brands in the business to power better mobility today and in the future. Our diverse global team of over 18,000 colleagues fosters an inclusive and collaborative culture, delivering a brilliant experience for our customers and partners.

The Digital Delivery Centres accelerate Inchcape’s digital journey by positively impacting the business and its customers through innovative and essential technological solutions. Through our top talents, we support the mobility of millions of people globally through the power of digital technology.

• Serve as a technical guide to the team and contribute to the overall MLOps infrastructure design
• Develop a playbook for MLOps Engineering and set global standards for managing MLOps activities across Inchcape
• Work closely with data scientists, business, and IT teams to build platform and framework to enable machine learning and data analytics activities ensuring robustness & scalability of solutions

• Scope, design, and implement machine-learning models to solve interesting user-cases and achieve measurable improvements
• Continuous innovation and optimization of machine learning workflow, through R&D on modern technologies.
• Collaborate with Data Science teams on model operationalization strategies
• Analytics-as-a-service is your mantra and develop relevant capabilities on the cloud to enable & monitor services based on the principles of Microservices
• Use containerization and cloud technologies (e.g. OpenShift, Kubernetes, Docker, Mesos, AWS) as well as DevOps and testing tools (Git, SVN, TFS, Jira, Confluence, Jenkins, Nexus, Selenium) to enable API economy

• Proven track record of leading high-performing data teams that successfully implemented real-time integration utilizing a variety of technologies, development tools and database systems.
• 5+ years of working experience in a hands-on ML role, including 2+ years of team leadership and people management.
• Master’s degree in Statistics, Machine Learning, Mathematics, Computer Science, Economics, or a related quantitative field; or a bachelor’s degree with at least 4 years of hands-on experience
• Strong background in machine learning, theory, and practice
• Experience building data pipelines, self-sufficient in obtaining data to build and evaluate models using tools like Apache Spark, PySpark or other distributed data processing frameworks
• Deep knowledge of SOA, architecture and design of microservices, REST Services Development
• Experience using cloud services such as Azure/Databricks is a plus

Build a brilliant career, where you’re encouraged and supported to fulfil your ambition, mentored by excellent managers. Explore exciting and rewarding career pathways, with regular promotion and performance reviews to help you progress. Develop your expertise and upgrade your skills with continuous training in the latest tech advancements.

If you have the skills, passion, and drive to thrive in this role, and you're ready to grow your career with a dynamic global team in the digital space, we want to hear from you

For any technical support please email to