Introduction
A career in IBM Software means you'll be part of a team that transforms our customers' challenges into industry-leading solutions.
We are an infinitely curious team, always seeking new possibilities, and dedicated to creating the world's leading AI-powered, cloud-native software solutions. Our renowned legacy creates endless global opportunities for our network of IBMers. We are a team of deep product experts, ensuring exceptional client experiences, with a focus on delivery, excellence, and obsession over customer outcomes.
IBM's product and technology landscape includes Research, Software, and Infrastructure. Entering this domain positions you at the heart of IBM, where growth and innovation thrive.
Your Role and Responsibilities
As an AI Technical Advocate, you will work closely with the IBM software development and sales teams to educate and promote IBM's enterprise AI features with clients. In this role, you will apply your technical expertise to understanding clients' business challenges and helping them explore how IBM's AI capabilities could solve those challenges effectively.
Architectural Leadership: Work collaboratively within a team responsible for shaping the architecture and technical trajectory of our AI portfolio.Domain Expertise: Possess a deep understanding of AI technologies and innovations including IBM's offerings and the competitive landscape.Collaboration and Adaptability: Collaborate seamlessly with diverse teams and contribute to other IBM product initiatives. A crucial aspect is the ability to extend expertise beyond your domain to promote a holistic understanding of interconnected domains.Effective Communication: Utilize strong communication skills to articulate complex technical concepts, fostering collaboration and understanding across interdisciplinary teams.Technical Solution Workshops: Conducting and participating in technical solution workshops.Required Technical and Professional Expertise Deep expertise in AI/ML model development and/or deployment of AI/ML workloads including experience in LLMs, Vector DBs, model tuning, and LLM benchmarking.Experience with building credibility for Data and AI methodology and practices for data management, data fabric, data governance, trustworthy AI, and business analytics or equivalent enterprise solutions.Proficient in Python programming, NLP techniques, and AI Frameworks (e.g., Hugging Face).Preferred Technical and Professional Expertise Architecting and deploying scalable AI solutions that integrate seamlessly with existing business and IT infrastructure.Experience designing & developing automated pipelines for data extraction, ML model training, ML model production deployments, and production monitoring.
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