Silicon Validation & AI/ML Architect
On-sitePune, Maharashtra, India
Job Summary
Lead silicon validation and AI/ML architecture for SoC, MCU, and connectivity product development, driving large technical initiatives across pre-silicon (simulation, emulation, FPGA) and post-silicon validation phases. Execute system-level validation, security, and functional safety concepts while performing debug and root-cause analysis across hardware, firmware, and software domains. Develop scalable validation automation frameworks using expert-level Python and C/C++, leveraging CI/CD, remote labs, and cloud-based infrastructures to optimize test coverage and engineering productivity. Apply AI/ML to failure analysis, root-cause prediction, and test optimization, defining an AI-first validation strategy. Requires 10+ years of semiconductor industry experience and a Master's or higher degree in Electrical, Computer, or related engineering fields.
Required Qualifications
- M.S./M.Tech/Ph.D. in Electrical Engineering, Computer Engineering, Computer Science, Artificial Intelligence, Machine Learning, or related field
- 10+ years of semiconductor industry experience
- Strong background in MCU, MPU, SoC, or Connectivity product development
- Proven experience in silicon bring-up, post-silicon validation, system validation, and product qualification
- Demonstrated leadership in driving large technical initiatives and cross-functional programs
- Deep understanding of: SoC architecture
- Deep understanding of: Embedded systems
- Deep understanding of: Silicon validation methodologies
- Deep understanding of: System-level validation
- Deep understanding of: Security and Functional Safety concepts
- Pre-silicon (simulation, emulation, FPGA) and post-silicon validation
- Expertise in debug and root-cause analysis across hardware, firmware, and software domains
- Expert-level Python development
- Strong C/C++ programming skills
- Experience developing scalable validation automation frameworks
- Knowledge of CI/CD, remote labs, cloud-based validation, and board farm infrastructures
- Ability to define and execute an AI-first validation strategy
Desired Qualifications
- Experience applying AI/ML to: Failure analysis
- Experience applying AI/ML to: Root-cause prediction
- Experience applying AI/ML to: Test optimization
- Experience applying AI/ML to: Coverage analysis
- Experience applying AI/ML to: Engineering productivity
- Knowledge of Digital Twin technologies and model-based validation approaches
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