Introduction
At IBM, work is more than a job - it's a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better, but to attempt things you've never thought possible. Are you ready to lead in this new era of technology and solve some of the world's most challenging problems? If so, lets talk.
#LI-hybrid
Your Role and Responsibilities
Architect end-to-end AI solutions by understanding business requirements, analyzing data, and identifying suitable AI algorithms and models. Design scalable and robust architectures that integrate AI capabilities into existing systems or new applications.
Technology Evaluation: Evaluate and select appropriate AI platforms, frameworks, and tools based on project requirements and industry best practices. Stay updated with the latest advancements in AI technologies and assess their potential for solving business problems.
Want more jobs like this?
Get jobs delivered to your inbox every week.
Data Analysis and Modeling: Collaborate with data scientists and data engineers to analyze large datasets, identify patterns, and develop machine learning models. Apply techniques such as supervised learning, unsupervised learning, and deep learning to extract insights and drive intelligent decision-making.
Integration and Deployment: Define integration strategies to seamlessly incorporate AI capabilities into existing systems or applications. Collaborate with development teams to ensure smooth deployment and integration of AI models, APIs, and services.
Performance Optimization: Identify performance bottlenecks and optimize AI models and algorithms for efficiency and scalability. Implement techniques such as model compression, parallel processing, and distributed computing to enhance system performance.
Security and Privacy: Ensure compliance with data privacy regulations and implement robust security measures to protect sensitive data used in AI solutions. Collaborate with cybersecurity teams to address potential vulnerabilities and mitigate risks.
Stakeholder Collaboration: Work closely with business stakeholders to understand their requirements, provide technical guidance, and translate business needs into AI solutions. Communicate complex technical concepts to non-technical stakeholders in a clear and concise manner.
Required Technical and Professional Expertise
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- Proven experience as a Solution Architect, with a focus on AI and generative AI technologies.
- Strong knowledge of machine learning algorithms, deep learning frameworks, and AI platforms.
- Proficiency in programming languages such as Python, R, or Java.
- Experience with cloud platforms, such as AWS, Azure, or Google Cloud, and their AI services.
- Familiarity with data engineering concepts, data pipelines, and data preprocessing techniques.
- Excellent problem-solving skills and the ability to think strategically and analytically.
- Strong communication and collaboration skills to work effectively with cross-functional teams and stakeholders.
Preferred Technical and Professional Expertise
-