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
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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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