Principal Engineer, Firmware Verification Engineering

Western Digital

8 - 12 years

40 - 45 Lacs

bengaluru

Posted:3 hours ago| Platform:

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Skills Required

rtos c++ automation asic usb linux kernel ethernet test planning pcie python

Work Mode

Work from Office

Job Type

Full Time

Job Description

Validate firmware for edge AI inference accelerators and storage devices with focus on AI framework integration (TensorFlow Lite, ONNX Runtime)
Design and execute test plans for low-level firmware functions, including bootloaders, memory management, task scheduling, and AI accelerators
Validate AI accelerator performance metrics including throughput, latency, and power efficiency for neural processing workloads
Interface with cross-functional teams (firmware, ASIC, hardware, systems) to isolate and debug firmware issues at the hardware/software boundary
Collaborate closely with firmware engineers & architects on product architecture and designs to define the comprehensive verification plan to deliver a high quality product to customers on time
Design, Develop and Integrate the white box and gray box tests on SSD products in roadmap inline with latest methodologies
Conduct test plan reviews and code reviews to ensure the tests are scalable and meeting the requirements
Contribute to continuous integration pipelines for automated testing and validation
Analyze test results, generate detailed bug reports, and drive resolutions with engineering teams
Document findings, contribute to root cause corrective action (RCCA) reports, and ensure closure of high-priority issues

Qualifications

Required Qualifications & Skills:

BE/B.Tech/ME/M.Tech degree in Electronics & Electrical Engineering, Computer Engineering or related field
Minimum 8+ years of experience in firmware development or validation for embedded systems
Experience with embedded processors, RTOS, memory interfaces, and microcontroller architectures including ARM Cortex-A/M series, ARC, and RISC-V CPU architectures
Proficiency in scripting and automation (Python, Bash) and familiarity with C/C++
Good understanding of communication interfaces such as I2C, SPI, UART, PCIe, Ethernet, and USB
Experience with AI framework validation (TensorFlow Lite, ONNX Runtime) and AI accelerator performance validation
Knowledge of AI workloads, neural processing units (NPUs), and AI accelerator architecture validation
Experience with benchmarking tools including MLPerf and AI benchmark suites for neural accelerator performance validation
Expertise in debugging and profiling AI workloads including neural network execution profiling on dedicated accelerators and performance bottleneck identification
Knowledge of Git, CI & source code management flow and agile development practices
Knowledge of Linux kernel drivers and debugging tools

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