Silicon Validation Engineer

Apple Inc.; Cupertino (CA); Hybrid; USD 150,000 - 225,000; Full time

Benefits offered by this job

Medical and dental coverage

Stock-based compensation

Relocation assistance

Tuition reimbursement

Employee stock purchase plan

Job summary

APPLE INC is seeking an experienced engineer to develop software for lab characterization and silicon validation in Cupertino, CA. You will work on embedded system software, including hardware bring-up, SPI/I2C/UART interfaces, and data-driven validation workflows.

You will design data pipelines, apply AI/ML models with PyTorch/TensorFlow, and build computer vision tooling to monitor lab equipment and automate chip handling. Collaboration across teams is essential.

Qualifications

• Master's degree or foreign equivalent in Electrical Engineering, Electronics Engineering, or a related field.
• Designing and analyzing electronic circuits, including analog, mixed-signal, and power circuits, to support validation and characterization of silicon IPs and subsystems.
• Designing embedded systems using microcontrollers or FPGAs, including experience with hardware bring-up, peripheral interfaces and low-level control.
• Programming in Python, C and Tcl to develop test automation scripts and lab tooling.
• Signal analysis and processing with time- and frequency-domain methods using NumPy, SciPy, and MATLAB.
• Data management pipelines using SQL databases to support silicon bring-up and tape-out decisions.
• AI/ML techniques with PyTorch or TensorFlow to develop predictive models and pattern recognition.
• PyTorch, TensorFlow and OpenCV for CNNs and computer vision in lab monitoring and chip handling.

Responsibilities

• Develop, maintain, and optimize software for lab characterization, validation, and debug of analog and mixed-signal circuits.
• Design embedded system software for lab instrumentation and test platforms with low-level hardware control.
• Develop data warehousing, visualization, and post-processing pipelines for large measurement data.
• Develop AI/ML solutions, including CNNs, for data analysis and pattern recognition in lab data.
• Develop computer vision pipelines for visual monitoring of lab equipment and chip handling.
• Leverage MPI, OpenMP, and CUDA to accelerate compute-heavy workloads on multi-core CPUs and GPUs.
• Integrate lab software with upstream design tools and automate test sequence conversion for end-to-end validation.

Skills

Python

C

Tcl

SQL

NumPy

SciPy

MATLAB

PyTorch

TensorFlow

OpenCV

CNNs

CUDA

MPI/OpenMP

Embedded systems

Education

Master's degree in Electrical Engineering or related field

Tools

SPI

I2C

UART

MATLAB

CUDA

PyTorch

TensorFlow

OpenCV

Job description

Cupertino, California, United States Hardware

Imagine what you can do here. Apple is a place where extraordinary people gather to do their lives best work. Together we create products and experiences people once couldn't have imagined, and now, can't imagine living without. It's the diversity of those people and their ideas that inspires the innovation that runs through everything we do.

Description

APPLE INC has the following available in Cupertino, California and various unanticipated locations throughout the USA. Develop, maintain, and optimize software for lab characterization, validation, and debug of analog and mixed-signal embedded circuits and silicon subsystems. Design and develop embedded system software for lab instrumentation and test platforms, including low-level hardware control, peripheral communication interfaces (SPI, I2C, UART), and hardware bring-up support for analog and mixed-signal test environments. Perform signal analysis and processing, including time-domain and frequency-domain analysis of analog and mixed-signal waveforms, to extract electrical parameters and support circuit characterization and validation. Design and implement data warehousing, visualization, and post-processing pipelines to manage and analyze large volumes of measurement data from lab bring-up and silicon characterization workflows. Develop artificial intelligence and machine learning solutions, including deep learning models and convolutional neural networks (CNNs), for post-silicon data analysis, predictive modeling, pattern recognition, and intelligent test and search algorithms. Develop and deploy computer vision pipelines for visual recognition, including automated monitoring of lab bench and equipment status and automated chip handling. Leverage parallel computing frameworks, including MPI, OpenMP, and CUDA, to accelerate compute-intensive signal processing, simulation, and machine learning workloads across multi-core CPU and GPU architectures. Apply software design principles, including algorithms and data structures, to architect scalable, maintainable, and reusable software components across lab tooling and validation infrastructure. Convert and adapt test sequences into formats compatible with lab software, and implement new software features in response to lab user requirements. Integrate lab software with upstream design tools and downstream system software, including establishing interfaces and automated test sequence conversion, to enable end-to-end silicon validation and characterization workflows. Provide debug support during lab bring-up and characterization, and resolve software-related issues and questions raised by lab users. 40 hours/week. At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $150,400 - $225,300/yr and your base pay will depend on your skills, qualifications, experience, and location.PAY & BENEFITS: Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits: https://www.apple.com/careers/us/benefits.html.Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Minimum Qualifications

• Master's degree or foreign equivalent in Electrical Engineering, Electronics Engineering, or a related field.
• Experience and/or education must include:
• Designing and analyzing electronic circuits, including analog, mixed-signal, and power circuits, to support validation and characterization of silicon IPs and subsystems.
• Designing embedded systems using microcontrollers or FPGAs, including experience with hardware bring-up, peripheral communication interfaces (SPI, I2C, UART), and low-level hardware control for lab instrumentation and test platforms.
• Utilizing programming and scripting languages, including Python, C and Tcl, to develop, optimize, and maintain test automation scripts, measurement utilities, and lab tooling for analog and mixed-signal validation workflows.
• Performing signal analysis and processing, including time-domain and frequency-domain analysis of analog and mixed-signal waveforms, using tools such as NumPy, SciPy, and MATLAB to extract electrical parameters and characterize circuit behavior.
• Designing and maintaining data management systems and pipelines, including collecting, storing, querying, and visualizing large volumes of measurement data using SQL databases and data analytics tools to support silicon bring-up and tape-out decisions.
• Applying artificial intelligence and deep learning techniques, including using frameworks such as PyTorch or TensorFlow, to develop predictive models and automate pattern recognition in analog and mixed-signal measurement data.
• Utilizing PyTorch, TensorFlow, and OpenCV to design and train deep learning models, including convolutional neural networks (CNNs), for automating pattern recognition on analog and mixed-signal measurement data and developing computer vision pipelines for visual monitoring of lab equipment and automated chip handling.

Preferred Qualifications

• N/A

This position is not subject to the application limits.

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