IBM Sustainability Software helps companies achieve their sustainability goals by infusing data with AI into daily operations enabled by expertise to deliver profit and purpose. This happens in five core areas: sustainability strategy, data, and reporting; energy transition and climate resilience; intelligent assets, facilities, and infrastructure; responsible computing and green IT; and sustainable supply chains and circularity. Each of these areas requires collecting data, making it visible and usable, and then acting on that data to drive sustainability outcomes. IBM offers a strong set of tools and products to support clients in their sustainability journey.
As a product manager for Geospatial AI within the IBM Environmental Intelligence product, you will drive the integration of geospatial models and development of tools and processes that enable developers to build custom models. This role will require close collaboration with research, engineering, data science, and customer-facing teams to ensure IBM is a leader in geospatial intelligence and environmental analytics.
Geospatial Dataset Strategy Development: Identify the necessary data customers need to build custom geospatial models efficiently. Develop strategies for integrating ground-truth data to improve model accuracy. Define a process for incrementally expanding datasets to address diverse customer use cases and geospatial challenges.
Advancing Geospatial AI: Drive the evolution of IBM’s geospatial APIs, ensuring seamless integration with geospatial foundation models and tooling for customization. Collaborate with the research and development teams to embed the latest studio capabilities into Environmental Intelligence.
Fine-tuning to support industry model creation: Design scalable methods for fine-tuning geospatial foundation models using open source and ground truth data to improve model accuracy and performance. Develop pathways that enable quick real-world applications of custom models in production.
Product Roadmap and Vision: Define and maintain the product vision and roadmap for geospatial foundation models and tooling for customization, ensuring alignment with the developer-first strategy for Environmental Intelligence. Prioritize features and enhancements to meet customer needs, market demands, and technical feasibility.
Stakeholder Collaboration: Partner with engineering, data science, and research teams to deliver high-quality, industry-specific models and tooling. Work with sales and CSMs teams to gather feedback and adjust product priorities to address customer challenges effectively.
Performance Metrics and Continuous Improvement: Establish key performance indicators (KPIs) to evaluate the impact and success of geospatial foundation models and fine-tuning tools. Leverage usage, customer satisfaction, retention, and use these insights to inform the product roadmap. Continuously monitor industry trends and emerging technologies to maintain IBM’s leadership in geospatial intelligence.
Bachelor’s degree in Computer Science, Data/ Environmental Science, or a related field
5+ years of experience in technical product management, preferably with APIs, AI/ ML
Experience working with technical geospatial APIs/ products, data types, sources, and integration techniques
Proven track record of launching, managing and scaling enterprise-grade AI tools designed for large-scale, production-level applications
Strong understanding of API technologies, data integrations, foundation models, developer tooling
Excellent communication and collaboration skills, with the ability to work cross-functionally in a fast-paced environment with cross-geographical teams
Analytical mindset with the ability to interpret market trends, customer feedback, and competitive insights
Experience with agile methodologies and tools (e.g., Jira) and collaborating with engineering teams
Master’s degree in Business Administration, Computer Science, or a related field
Proficiency in machine learning frameworks and AI platforms (e.g., PyTorch, or similar)
Experience managing end-to-end AI product lifecycles, from ideation to deployment
Hands-on experience collaborating with data science teams to integrate customer data for model tuning and performance optimization