Jobs for People with MS: National MS Society

Introduction

At IBM, we're revolutionizing our approach to technology sales. Our Client Engineering teams are champions of co-creating solutions in real-time to solve complex business challenges.

As an AI Engineer within our Client Engineering team, you'll harness your unique skills and perspectives to engage in the development and deployment of AI systems using our watsonx platform, creating 4-to-6-week pilots for clients, and contributing to IBM's story of growth and innovation.

In this role, you'll partner with technical leaders across IBM and drive client engagements with a curiosity that sparks innovation and learning. Your contributions will form a cornerstone in our sales strategy, facilitating rapid client delivery and product innovation.

At IBM the possibilities are endless. We offer extensive onboarding and ongoing development, fostering an environment where you can thrive and shape your own career trajectory. Surrounded by a supportive team, you'll be integral in creating user-centric, compelling pilots that lead clients to continually invest in IBM's people, products, and services.

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.

We are committed to your success. If this role aligns with your career. Your typical day as AI Engineer may look like:

• Leverage contemporary data science skills (e.g., Machine Learning/Deep Learning, analytics, GenAI, data engineering, data pipeline, ETL) with industry expertise and an understanding of your clients’ businesses.

• Define and communicate the unique value of IBM’s technology, both technically and commercially.

• Collaborate with the broader IBM team and participate in client sessions that include a range of data, AI and cloud technologies.

• Support the solutions architecture plan and be a hands-on "builder" during client-facing engagements.

• Advice on solution architecture to align with AI/ML/data science best practices, with a focus on our clients target environment to ease transition to deployment.

• Work with deployment teams to transition AI/ML/data science assets and information to provide seamless transitions for our clients.

• Build data pipelines and processes for data ingestion, cleaning, and transformation, ensuring high-quality datasets for downstream AI tasks.

• Design, train, and optimise traditional and generative AI models to demonstrate business value to clients using IBM technologies.

• Integrate AI solutions / model outputs into existing systems where applicable for deployment.

Required technical and professional expertise

• Hands-on experience with a wide range of cloud and AI technologies.

• Practical knowledge and direct experience with data science, ML, and GenAI technologies.

• Experience in building data science project or AI/GenAI application across different use cases.

• Technical experience in various data science / AI / GenAI technology such as watsonx, Llama, OpenAI, Gemini, Claude, PyTorch, LangChain, LangGraph, Streamlit, Sparks, Presto, Hadoop, Chroma, Milvus and so on.

• Technical experience in various databases such as RDBMS, NoSQL, Graph Databases, etc.

• Familiar with data management processes such as ETL, ELT, data replication, etc.

• Understanding and practical application of Agile best practices.

• Proficient in Python.

Preferred technical and professional experience

• Experience in end-to-end model development lifecycle from model development to deployment to monitoring to model refresh.

• Familiar with concepts and good understanding of model risk governance

• Relevant technical certifications (Machine Learning, Data Science, AI certifications)