At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology.

Job Description:

This role centers on developing mathematical and probabilistic algorithms that enhance the accuracy, robustness, and performance of Cadence’s simulation and analysis tools. The engineer will work on numerical methods, stochastic modeling, statistical analysis, and algorithmic innovations that support next‑generation EDA technologies. The position also includes building internal tools to streamline research and development workflows.

Responsibilities:

• Design and implement mathematical algorithms for simulation, modeling, and statistical analysis

• Apply probabilistic theory to improve accuracy and convergence of simulation engines

• Develop numerical methods for large‑scale computation and optimization

• Collaborate with software engineers and domain experts to integrate mathematical models into production systems

• Build scripts and tools to support internal R&D processes

• Validate algorithmic correctness through experiments, benchmarks, and data analysis

Requirements

• Strong foundation in applied mathematics, probability theory, and numerical methods

• Proficiency in Python and C

• Experience with scientific computing libraries or frameworks is a plus

• Familiarity with Linux/Unix development environments

• MS in Applied Mathematics, Statistics, Computer Science, Electrical Engineering, or related fields

• Strong analytical thinking and ability to translate mathematical concepts into practical software solutions

• Good communication skills and ability to work effectively in a collaborative environment

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