IBM

IBM Client Engineering - AI Engineers 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. AI Engineers 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. 

You will have below role focus in order to become a successful AI Engineer in Client Engineering team.

• Technical Expertise
  • Creating and managing the AI development.
  • Define strategies and plan for development on production infrastructure.
  • Fine-Tune, Deploy and Operate Foundation Models. 
  • Optimizing AI infrastructure to drive measurable business value for customers.
  • Building AI models from scratch& Fine Tuning pre-trained models and assisting different stakeholders with analysis and implementation. 
  • Transforming machine learning models into APIs that can be integrated with other applications. 
  • Collaborating across teams to help with AI adoption and best practices.
• Engagement
  • Use prior experience in AI project and domain to gain client trust
  • Apply Foundation Models to propose and validate hypotheses for business queries.
  • Collaborate with the client to rapidly develop AI solutions using IBM watsonx Platform via a Proof of Experience (PoX).
  • Employ Agile methodologies for responsive AI solution development based on client feedback.
• Strategic Innovation
  • Utilize 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. 
  • Suggest improvements for data reliability, efficiency, and quality in future projects, using proficiency in programming, big data technologies, and AI frameworks. 
  • Display a growth mindset and genuine curiosity to grasp clients' business processes and challenges, employing statistical analysis skills to identify transformation opportunities. 
  • Employ agile methodologies to hasten solution definition and validation, enhancing client outcomes swiftly. 

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

1. Strong contribution record demonstrated through active participation in open source communities, sharing technical resources and educational content, maintaining influential technical blogs or social media presence, and public evangelism of technology through speaking engagements, workshops and community events.
2. Track record in being part of highly collaborative teams to tackle important problems which produce high impact solutions.
3. Expertise in Python programming and statistical analysis including experience with advances statistical methods, data modeling and implementing efficient algorithmic solutions.