Company:

Qualcomm Semiconductor Limited

Job Area:

Engineering Group, Engineering Group > Hardware Engineering

General Summary:

Drives the vision, strategy, architecture, and execution of enterprise-scale Machine Learning, Data Analytics, Data Governance, AI solutions and Engineering Productivity Tool initiatives. Is responsible for the development of scalable AI/ML platforms, data ecosystems, governance frameworks, analytics solutions, and software tools that accelerate engineering productivity, improve business decision-making, and enable data-driven innovation across the organization.

Develops and executes long-term strategies for Global AI adoption, advanced analytics, data infrastructure, and governance capabilities. Collaborates with engineering, operations, IT, quality, reliability, business groups, and executive leadership to transform data into actionable insights and scalable solutions. Coordinates and oversees the adoption of enterprise platforms, intelligent workflows, predictive analytics, AI-powered applications, and governance frameworks that improve efficiency, quality, velocity, and business outcomes.

The Responsibilities Of This Role Include:

Working in alignment to leadership's priorities, vision and strategies with minimal executive oversight.
Providing supervision to managers and senior technical leaders who may be direct reports.
Making decisions in alignment with global leadership that have significant organizational, operational, financial, and strategic impact across multiple functions and geographies.
Influencing global organizational strategy, technology direction, and business priorities through data-driven insights and technical leadership.
Communicating highly complex technical, business, and organizational concepts to executives, customers, partners, and engineering organizations.
Leading large-scale transformations related to AI, machine learning, data management, governance, automation, and engineering productivity.
Establishing long-term global roadmaps and investment strategies for AI platforms, analytics frameworks, data ecosystems, and software tooling.
Driving innovation through the application of machine learning, generative AI, predictive analytics, workflow automation, and intelligent decision-support systems.
Defining governance models, policies, standards, and best practices for data quality, security, responsible AI, compliance, access control, and lifecycle management.
Using advanced analytical thinking, systems-level problem solving, and strategic planning to address highly ambiguous business and technical challenges.

Additional Responsibilities May Include

Developing enterprise AI strategy and governance frameworks.
Driving adoption of Generative AI, Agentic AI, Knowledge Management, and Intelligent Automation solutions.
Developing enterprise data lake, warehouse, semantic layer, and analytics architectures in collaboration with IT and Knowledge teams.
Leading digital transformation initiatives involving cloud platforms, data platforms, MLOps, and DataOps.
Creating metrics and value frameworks to measure business impact from AI and analytics investments.
Defining enterprise standards for AI model lifecycle management, governance, security, and compliance.

Minimum Qualifications

Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, Information Systems, or related technical field.
12+ years of experience in Machine Learning, Data Analytics, Software Engineering, Data Engineering, AI Platforms, or related disciplines.
5+ years of leadership experience managing managers, technical leaders, or large cross-functional organizations.

OR

Master's degree in Computer Science, Data Science, Engineering, Statistics, Artificial Intelligence, or related field and 10+ years of relevant experience.

OR

PhD in Artificial Intelligence, Machine Learning, Computer Science, Engineering, Statistics, or related field and 8+ years of relevant experience.

Preferred Qualifications

Experience leading enterprise-scale AI/ML and advanced analytics programs.
Experience with cloud and big data platforms such as Databricks, Snowflake, AWS, Azure, GCP, or similar technologies.
Knowledge of MLOps, DataOps, platform engineering, and enterprise data governance frameworks.
Experience developing Generative AI, LLM, Agentic AI, and intelligent workflow solutions.
Proven ability to lead large-scale organizational transformation initiatives.
Strong understanding of data privacy, security, compliance, and responsible AI principles.
Experience operating in highly technical engineering organizations supporting product development and manufacturing operations.

Minimum Qualifications:

Bachelor's degree in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 8+ years of Hardware Engineering or related work experience.

OR

Master's degree in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 7+ years of Hardware Engineering or related work experience.

OR

PhD in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 6+ years of Hardware Engineering or related work experience.

Applicants: Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail [HIDDEN TEXT] or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).

Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.

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