Machine Learning Operations Manager

Machine Learning Operations ManagerOur client is an automotive supplier and partner to automakers worldwide. As a technology company, they design innovative solutions for smart mobility, with a particular focus on safer driving and reducing CO2 emissions.Their mission is to deliver market-leading perception solutions for ADAS driving and parking functions. Through their state-of-the-art, data-driven approach, they harness the expertise of the company's global community to provide safe, reliable, and innovative perception solutions.They aim to develop and deliver a modular, scalable, and hardware-agnostic full perception stack, utilising the company's technology leadership in sensing and ADAS computing platforms.Requirements➔ Lead the ML Ops team globally➔ Develop end-to-end (Data/Dev/ML) Ops pipelines based on in-depth understandingof 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 andAutonomous Driving perception applicationsYour Responsibilities➔ Co-ordinate a dedicated global team of software engineers to develop and manageMLOps tools that help automate and improve our deep learning softwaredevelopment and model building practices➔ MLOps Strategy: Develop and implement MLOps strategies, roadmaps, bestpractices, and standards to enhance AI ML model deployment and monitoring➔ Infrastructure Management: Oversee the design, deployment, and management ofscalable and reliable infrastructure for model training and deployment, bothon-premise and on the cloud➔ Monitoring and Optimization: Create and maintain robust monitoring systems to trackmodel 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, andSW engineers to support smooth integration of ML models into production systems➔ Stakeholder Engagement and Collaboration: Collaborate closely with business andPM stakeholders in roadmap planning and implementation efforts and ensuretechnical milestones align with business requirementsEducation/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/orupdating 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