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Principal Enterprise AI/ML Architect
2 months ago
- Develop and maintain a comprehensive enterprise architecture for AI/ML/GenAI initiatives, ensuring alignment with Qualcomm's overall business strategy and technology roadmap.
- Assess current state AI/ML/GenAI capabilities across various business domains, identify gaps, and design target state architectures to drive innovation, revenue growth and operational excellence.
- Lead transformational initiatives to bridge the gap between current and desired AI/ML capabilities, collaborating with cross-functional teams to ensure successful implementation.
- Establish governance frameworks and decision criteria for AI/ML and GenAI projects, ensuring adherence to industry standards, regulatory requirements, Responsible AI and Qualcomm's architectural principles.
- Create and maintain reference architectures, patterns, and best practices for AI/ML lifecycle and integration within Qualcomm's enterprise ecosystem.
- Lead the technology evaluation and process improvements to drive Experimentation, Model Development and ML Ops at scale.
- Lead and drive standardization of LLM onboarding process, RAG pipelines and application development.
- Conduct architecture reviews and risk assessments for proposed AI/ML solutions, ensuring they meet security, scalability, and interoperability requirements.
- Utilize advanced data science techniques (e.g., Natural Language Processing, clustering, predictive analytics, regression analyses, survival analysis, segmentation, and experimentation) to propose enhancements and innovations to business processes.
- Conduct sophisticated statistical analyses and maintain high reliability of machine learning pipelines in production environments, ensuring minimal downtime and optimal performance.
- Collaborate with business leaders to identify opportunities for AI/ML-driven innovation and guide the development of use cases that deliver tangible business value.
- Oversee the design and implementation of data pipelines and AI/ML models, ensuring they integrate seamlessly with existing enterprise systems and processes.
- Develop strategies for data governance, quality, and management to support AI/ML initiatives across the organization.
- Influence executive and senior leadership on the strategic adoption of AI/ML technologies and their impact on business processes and outcomes.
- Foster a culture of continuous learning and innovation in AI/ML practices across the enterprise architecture team and broader organization.Minimum Qualifications:
- Master's Degree in Computer Science, Information Systems, Data Science, or a related field.
- 8+ years of experience in enterprise architecture, with a focus on AI/ML integration and transformation projects.
- Proven experience in leading enterprise-wide transformations of AI/ML capabilities.
- Strong understanding of enterprise architecture frameworks (e.g., TOGAF, Zachman) and modeling languages (e.g., ArchiMate).
- Proficiency in data architecture and AI/ML technologies (AI Orchestration, Feature stores, ML observability, etc.), frameworks, and their application in enterprise setting.
- Experience with cloud computing platforms (AWS, GCP, Azure) and their AI/ML offerings.
- Excellent communication skills, with the ability to articulate complex architectural concepts to both technical and non-technical stakeholders.
- Demonstrated leadership in driving cross-functional initiatives and facilitating organizational change.
- Player coach mindset with excellent collaboration skills to drive pragmatic changes.Preferred Qualifications:
- PhD in Data Science/Machine Learning, Mathematics/Statistics, Computer Science, or a closely related field.
- TOGAF certification and ArchiMate 3 Practitioner Certification.
- Experience in the semiconductor industry or related high-tech manufacturing environments.
- Proficiency in programming languages relevant to AI/ML (e.g., Python, R) and data manipulation (SQL, NoSQL).
- Familiarity with advanced AI/ML techniques, including deep learning, NLP, and generative AI models.
- Experience with business architecture and business capability modeling.
- Strong background in information security architecture and data privacy principles.
- Proven track record of successful large-scale AI/ML transformations in enterprise settings.Education Requirements:
- Master's Degree in Cognitive Science, Data Science/Machine Learning, Statistics, Mathematics, Computer Science, or a related field is required.A PhD in the aforementioned fields is strongly preferred.
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- Master's Degree in Cognitive Science, Data Science/Machine Learning, Statistics, Mathematics, Computer Science, or a related field is required.A PhD in the aforementioned fields is strongly preferred.
