Associate Engineer – CAD AI/ML

Skills this role screens for

About the role

Qualcomm is hiring for the role of Associate Engineer – CAD AI/ML!

The work

Responsibilities of the Candidate

• Develop scripts, utilities, and automation solutions for CAD and design workflows.
• Apply machine learning and data analytics techniques to CAD data, tool logs, reports, and engineering metrics.
• Assist in building models for:
• Tool runtime and resource prediction
• Failure classification and root-cause analysis
• Log analysis and anomaly detection
• Quality and performance trend analysis
• Flow optimization and productivity improvement
• Process and analyze large datasets generated by EDA tools and semiconductor design flows.
• Develop data-preprocessing pipelines for extracting meaningful information from logs and reports.
• Support the integration of AI/ML models into existing CAD automation frameworks and engineering tools.
• Collaborate with CAD, RTL, verification, synthesis, physical design, and methodology teams.
• Debug scripts, data pipelines, and model-related issues.
• Create dashboards, reports, and visualizations to communicate engineering insights.
• Conduct experiments, evaluate model performance, and document results.
• Follow software development best practices, including version control, testing, code reviews, and documentation.
• Stay current with developments in AI/ML, automation, and semiconductor design technologies.

Who they want

Requirements

• Bachelor’s degree in Computer Science, Information Technology, Artificial Intelligence, Machine Learning, or a related field.
• 0–1 year of experience in software development, CAD automation, data analytics, or AI/ML.
• Strong programming skills in Python.
• Good understanding of:
• Data structures and algorithms
• Object-oriented programming
• Machine learning fundamentals
• Statistics and probability
• Data preprocessing and analysis
• Linux/Unix environments
• Database concepts and SQL
• Familiarity with Python libraries such as NumPy, Pandas, Scikit-learn, and Matplotlib or similar tools.
• Ability to read, analyze, and troubleshoot software logs and engineering reports.
• Strong analytical and problem-solving skills.
• Good written and verbal communication skills.
• Ability to work effectively in a multidisciplinary engineering environment.
• Academic projects, internships, or coursework in AI/ML, data science, or automation.
• Familiarity with TensorFlow, PyTorch, Keras, or other ML frameworks.
• Knowledge of natural language processing, generative AI, large language models, or retrieval-augmented generation.
• Exposure to semiconductor design and verification concepts, including:
• RTL and SystemVerilog
• Synthesis and implementation flows
• Static analysis, formal verification, or simulation
• Design-for-test and low-power methodologies
• EDA tools and CAD flows
• Experience working with structured and unstructured engineering data.
• Familiarity with Git, REST APIs, CI/CD, Docker, or cloud-based development environments.
• Exposure to shell scripting, Perl, Tcl, or other automation languages.
• Understanding of software testing and automation methodologies.