Principal Data & AI Architect
On-siteWaukesha, Wisconsin, United States
Job Summary
Design and implement advanced Data & AI architectures, including enterprise data/MDM solutions, machine learning models, deep learning frameworks, and generative AI systems. Analyze, deploy, and optimize these solutions across on-premises and cloud environments while defining technical strategies and roadmaps. Collaborate with cross-functional teams to integrate scalable, secure, and efficient AI systems into production, advising on technology adoption and leading technical mentorship. Translate complex technical concepts for non-technical stakeholders and communicate industry trends to maintain a competitive edge. This individual contributor role requires an advanced degree and 8+ years of experience in AI and data science.
Required Qualifications
- Advanced degree (Master's or Ph.D.) in Computer Science, Artificial Intelligence, Machine Learning, or a related field
- 8 or more years of experience in AI, machine learning, or data science
- At least 4 years in a senior or lead architect role
- Proven track record of designing and deploying large-scale Data & AI systems in production environments
- Experience leading cross-functional teams in the delivery of complex AI projects
- Hands-on experience with cloud platforms (e.g., AWS, Azure, Google Cloud)
- Hands-on experience with AI frameworks (e.g., TensorFlow, PyTorch, scikit-learn)
- Expertise in machine learning algorithms
- Expertise in Neural networks
- Expertise in Genetic Algorithms
- Expertise in Decision trees
- Expertise in Business dynamic models
- Expertise in Agent based models
- Expertise in Advanced statistical techniques and operations research
- Strong proficiency in programming languages such as Python, R, or Java
- Ability to design scalable, secure, and efficient AI architectures
- Exceptional problem-solving and analytical skills
- Strong leadership and mentorship abilities
- Excellent communication skills, capable of translating technical concepts to diverse audiences
- Ability to work in a fast-paced, dynamic environment and manage multiple priorities
- Occasional travel
Desired Qualifications
- Ph.D. In Operations Research, Data Science, or a closely related field
- Master's degree in a relevant field with significant research or project work in AI or machine learning
- Relevant certifications such as AWS Certified Machine Learning – Specialty, Google Professional Machine Learning Engineer, or Microsoft Certified: Azure AI Engineer Associate
- Experience with generative AI and reinforcement learning
- Publications or patents in AI, machine learning, or related fields
- Familiarity with DevOps practices and MLOps pipelines for AI deployment
- Experience in industries such as healthcare, finance, or technology
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