Head of Machine Learning Operations (MLOps) in South West London - RBW Consulting

Job DescriptionA great opportunity has arisen to join an innovative team at the forefront of cutting-edge technology. This pivotal role calls for an expert adept in harnessing AI products, overseeing ML development standards, and driving strategic improvements to business processes and systems. As part of this role, you'll collaborate closely with multifaceted data teams, shape and lead high-performance MLOps teams, and champion the deployment of AI/ML solutions within a dynamic, growth-oriented environment.If you're driven by innovation, possess a keen eye for process enhancement, and thrive in fostering a culture of excellence, this opportunity offers an ideal platform to leverage your expertise and drive impactful change.Responsibilities:Resource Management: Allocate skillful resources for AI product delivery, collaborate with managers within the data organization.Team Building: Assemble a top-notch MLOps team and establish ML development standards.Strategy and Communication: Engage with leadership to craft the team's roadmap, communicate it effectively within and outside the team.Process Optimization: Develop efficient processes for optimal team performance and create reusable assets and frameworks.Technical Oversight: Design cloud-based ML products, supervise app development, and validate solutions.Expert Guidance: Provide expertise in cloud architecture and DevOps for AI operationalization, lead end-to-end development pipelines.Innovation and Learning: Research new technologies, innovate through prototypes, and seek solutions for complex problems.Stakeholder Collaboration: Work closely with stakeholders, support lifecycle management, and oversee projects' execution.Team Leadership: Lead, mentor, and nurture a team of skilled engineers and tech leads.Requirements:Experience: Over 10 years in consulting, tech leadership, and AI/ML development.Skills: Proficiency in MLOps, CI/CD pipelines, and agile development practices.Expertise: Background in data science, software engineering, and design thinking.Management: Demonstrated leadership, coaching, and stakeholder management skills.Technical Aptitude: Hands-on experience in AI/ML development, deployment, and lifecycle management.Adaptability: Ability to assess new technologies and drive innovation.