Qualcomm's Applied ML R&D for HW Design team aims to solve challenging problems in chip design by developing ML/AI or algorithmic based design tools to improve the overall chip design process and quality through NRE and/or AuC reduction or performance improvement.
Requirements
- Strong background in machine learning, deep learning, and statistical modeling.
- Proficiency in programming languages such as Python.
- Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Familiarity with software development best practices and version control systems like Git.
- Hands-on experience with Generative AI models (e.g., LLMs, diffusion models).
- Experience with big data technologies such as Hadoop, Spark, and cloud platforms like AWS, Azure, or Google Cloud.
Responsibilities
- Work in a team of ML, CAD, and HW engineers to deliver technologies which compose a multi-component system
- Explore and define technical solutions to meet system requirements.
- Work closely with your co-developers to ensure seamless integration and alignment across all components in the overall system.
- Collaborate with a cross-functional team of hardware engineers, CAD engineers, and IT engineers to integrate AI-driven solutions into the chip design pipeline
- Conduct Exploratory Data Analysis (EDA) to uncover insights and inform model development.
- Develop advanced models and algorithms to solve complex problems.
- Perform feasibility studies to assess the viability of proposed solutions.
Other
- Master's or Ph.D. degree in Computer Science, computer engineering, Electrical Engineering, Statistics, or a related field.
- Excellent problem-solving skills and the ability to work independently and as part of a team.
- Proven ability to conduct feasibility studies and explore technical solutions.
- Ability to test and evaluate solutions against metrics and benchmarks.
- Excellent communication skills to collaborate effectively with cross-functional teams.
