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Machine Learning Solutions Architect
2 months ago
About Haleon
Haleon is a world-leading consumer health company that is shaping the future of everyday health for billions of people. We are a unique combination of deep human understanding and trusted science, with a portfolio of category-leading brands such as Sensodyne, Panadol, Advil, Voltaren, Theraflu, Otrivin, and Centrum.
About the Role
We are seeking a motivated and experienced Senior AI/ML Architect to join our Data Architecture and Platforms team. In this role, you will be essential in transforming the needs of our business and machine learning engineers into scalable and effective AI/ML solutions.
Key Responsibilities
- Translate business and machine learning engineer requirements into scalable and efficient AI/ML solutions.
- Ensure AI/ML solutions are strategically aligned with Haleon's goals, contributing to measurable business impact.
- Lead in designing, building, and managing a comprehensive AI/ML architecture, maintaining end-to-end accountability.
- Collaborate with the Principal AI/ML Architect to establish AI/ML architecture frameworks and design standards.
- Engage with various business functions, regions, tech partners, and architects to support and drive AI/ML initiatives across Haleon.
- Focus on enhancing AI/ML capabilities and efficiencies, keeping abreast of latest trends and technologies in the field.
- Collaborate with Data Architects, Tech Solution Architects, and Enterprise Architects to ensure the enterprise view of AI/ML is represented accurately within an application or solution scope.
Why You?
We are looking for professionals with the following required skills:
- Bachelor's or Master's degree in Computer Science with a total experience of 5-8 years.
- Proven track record in AI/ML architecture, with substantial experience in data architecture and modeling.
- Strong proficiency in AI/ML technologies and tools, with the ability to integrate them into scalable solutions.
- Excellent communication abilities, with a talent for bridging the gap between technical and non-technical stakeholders.
- Ability to align AI/ML solutions with broader business strategies and adapt to evolving organizational needs.
- Demonstrated success in working collaboratively across different functions and cultural boundaries within an organization.