Artificial Intelligence Engineer

Introduction

Technology sales at IBM is evolving its way of working to break beyond boundaries with innovative approaches. Preferring to ‘show’ vs. ‘tell’, Client Engineering co-creates with prospective customers, in real-time, on solutions to their hardest business challenges. As an AI Engineer within a Client Engineering squad, you’ll contribute to the co-creation of Proofs of Value (PoV) and Minimal Viable Product that demonstrate business value, leading to client investment in AI strategic solutions using Foundation Models. You will engage in developing and deploying AI systems to solve real-world business problems in a wide array of industries around the globe using IBM watsonx platform. AI Engineers cover all stages of the AI solution lifecycle from Data Engineering to Train, Validate, Tune, Deploy, AI Operations, and AI Governance to create a trusted end-to-end AI solution.

As an AI Engineer within a Client Engineering squad, you’ll partner with Technical Leaders across IBM sales teams and specialists to drive these experiential client engagements. You will form a sales cornerstone in partnership with Development, Research and Sales for rapid client delivery and product innovation.

Excellent onboarding training will set you up for success, whilst ongoing development will continue to advance your career through its upward trajectory. Our sales environment is fast-paced and supportive. Always connected to a wider team, you’ll be surrounded by other leaders and colleagues who are always willing to help and be helped – as you steer the creation of MVPs and proofs of concept (PoC) that obsess over user-centricity and business impact. All-the-while ensuring your teams are compelling clients to continually invest in IBM’s people, products, and services.

Your Role and Responsibilities

An AI Engineer in Client Engineering is a specialist in Foundation Models and building AI systems. You’ll leverage the watsonx platform with clients to co-create the value AI can bring to business. You will focus on Technology Patterns as our way to build the right skills and assets for repeatability to delight clients. AI Engineers work in high touch environment on all watsonx.ai opportunities.

To Help Ensure This Win-win Outcome, a 'day-in-the Life' Of This Opportunity May Include, But Not Be Limited To

• Fine Tuning pre-trained Foundation Models and assisting different stakeholders with analysis and implementation.
• Apply prompt-engineering techniques to specific use cases and types of models.
• Collaborating with the client to rapidly develop AI solutions using IBM watsonx Platform via a Proof of Experience (PoX)
• Applying Foundation Models to propose and validate hypotheses for business queries
• Utilizing the latest IBM AI technical strategies and sales plays to unlock client opportunities, applying skills in AI development, model building, Fine-Tuning and API integration.
• Displaying a growth mindset and genuine curiosity to grasp clients' business processes and challenges, employing statistical analysis skills to identify transformation opportunities.

Required Technical and Professional Expertise

• Understanding of key concepts in the Foundation Models literature and expertise in building and deploying them for real-world examples.
• Knowledge of cloud technologies, specifically Kubernetes, and expertise in leveraging them for large-scale AI workloads.
• Ability to identify fundamental problems from real-world cloud use-cases and to design, build and validate successful AI solutions.
• Capability to demonstrate and evaluate AI solutions via experimental methods, particularly through hands-on creation of prototypes.
• Strong communication skills and the ability to collaborate effectively within a local team.
• Excellent command of the English language, both verbal and written.

Preferred Technical And Professional Expertise

• Strong contribution record with either publications in top peer-reviewed scientific conferences and journals or strong leadership track-record in opens source communities, with a particular focus on foundation models, or large scale machine learning models.
• Track record of being part of highly collaborative teams to tackle important problems which produce high impact solutions.