Senior Machine Learning Project Manager

About the role

As a Machine Learning Project Manager, you will have the opportunity to collaborate with machine learning engineering, machine learning operations engineering, data platform and product teams to define project scope, establish timelines, and allocate resources to ensure the successful implementation and delivery of machine learning solutions and the platform that supports them.

Responsibilities

• Own and Prioritise the Machine Learning development backlog
• Define and prioritize features, enhancements, and functionalities for the machine learning products and platform based on user analysis, stakeholder feedback, and business requirements.
• Collaborate with machine learning leadership and internal stakeholders to understand their needs, gather feedback, and incorporate it into planning and development processes.
• Plan and oversee release, ensuring effective communication, documentation, and training to drive product adoption and success.
• Help establish processes and workflows, closely monitor progress, and take proactive measures to address any potential issues that might affect delivery timelines.
• Coordinate testing, validation, and quality assurance processes to ensure the accuracy and reliability of machine learning solutions.
• Define key metrics, establish monitoring systems, and regularly evaluate and report on the performance and success of the AI/ML platform.
• Support the ML Teams in transitioning to the new ways of working while driving continuous improvement by suggesting processes upgrades.

Key Qualifications

• BA in computer science, information systems, data science, or related field.
• 4+ years of experience as a Product Manager, Project Manager, Program Manager, Product Owner in the ML / Data space.
• Good communication skills
• Strong knowledge of Agile methodologies required.
• Good knowledge of applicable project management tools and technology required (ideally Jira).
• Experience with machine learning products, and understanding of how machine-learning systems work.
• Able to balance working for tactical gain with progressing towards a long term vision, with a bias for action
• Interest in Data Engineering (desired but not required)

Why Onclusive?

• Collaborative Environment: Thrive in an inclusive and supportive atmosphere where your ideas are valued.
• Professional Growth: Take advantage of mentoring opportunities and explore novel dimensions of your skillset.
• Cutting-Edge Tech: Immerse yourself in the latest advancements in machine learning.
• Impactful Work: Contribute to solving real-world challenges and be a central piece of Onclusive’s innovative strategy.