Advisory AI Engineer

Your role and responsibilities An AI Engineer at IBM is not just a job title - it's a mindset. You'll leverage the watsonx platform to co-create AI value with clients, focusing on technology patterns to enhance repeatability and delight clients. Success is our passion, and your accomplishments will reflect this, driving your career forward, propelling your team to success, and helping our clients to thrive. Day-to-Day Duties: Proof of Concept (POC) Development: Develop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Collaborate with development teams to implement and iterate on POCs, ensuring alignment with customer requirements and expectations. Collaboration and Project Management: Collaborate with cross-functional teams, including data scientists, software engineers, and project managers, to ensure smooth execution and successful delivery of AI solutions. Effectively communicate project progress, risks, and dependencies to stakeholders. Customer Engagement and Support: Act as a technical point of contact for customers, addressing their questions, concerns, and feedback. Provide technical support during the solution deployment phase and offer guidance on AI-related best practices and use cases. Documentation and Knowledge Sharing: Document solution architectures, design decisions, implementation details, and lessons learned. Create technical documentation, white papers, and best practice guides. Contribute to internal knowledge sharing initiatives and mentor new team members. Industry Trends and Innovation: Stay up to date with the latest trends and advancements in AI, foundation models, and large language models. Evaluate emerging technologies, tools, and frameworks to assess their potential impact on solution design and implementation. Required education Bachelor's Degree Preferred education Master's Degree Required Technical and Professional Expertise Education: Bachelor's, Master's, or Ph.D. degree in Computer Science, Artificial Intelligence, Data Science or a related field. Technical Skills: Strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, Keras or Hugging Face. Understanding in the usage of libraries such as SciKit Learn, Pandas, Matplotlib, etc. Familiarity with cloud platforms (e.g. Kubernetes, AWS, Azure, GCP) and related services is a plus. Soft Skills: Excellent interpersonal and communication skills. Engage with stakeholders for analysis and implementation. Commitment to continuous learning and staying updated with advancements in the field of AI.