Principal Software Engineer - Circuit Simulation R&D

San Jose, CA, US • Posted 30+ days ago • Updated 2 hours ago

Full Time

On-site

USD $136,500.00 - 253,500.00 per year

Fitment

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Job Details

Skills

Research and Development
Cadence
Mathematics
FOCUS
Design Of Experiments
Reliability Analysis
Modeling
CHAOS
Applied Mathematics
Derivatives
Elasticsearch
Numerical Analysis
Linear Algebra
Software Engineering
Probability
Data Science
Machine Learning (ML)
Regression Analysis
Support Vector Machine
Solaris Volume Manager
k-nearest neighbors
Artificial Intelligence
Active Learning
Python
C++
NumPy
PyTorch
JAX
Performance Tuning
Computer Science
Data Structure
Version Control
Testing
Continuous Integration
Continuous Delivery
HPC
Parallel Computing
MPI
CUDA
Workflow
Computational Science
Dynamics
Computational Physics
Electrical Engineering
Electronic Design Automation
EDA
Data Analysis
SPICE
Verilog
Monte Carlo Method
Research Design
Algorithms
Estimating
Optimization
Statistics
Collaboration
Sales

Summary

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

We seek a graduate researcher-practitioner in applied mathematics/statistics to advance algorithms for electronic circuit simulation, Monte Carlo yield analysis, and optimization. You will work cross-functionally to turn deep math into production-grade technology.

Qualifications

Graduate degree in applied mathematics, statistics, or a closely related field (CS with strong math focus).
Demonstrated ability to conduct literature reviews, translate theory to practice, and deliver innovative results in real-world settings.

Core Expertise

Statistical inference: significance testing (p-values, confidence intervals), Bayesian statistics, design of experiments, Monte Carlo methods (random sampling, density estimation).
Rare-event and reliability analysis (a plus): importance sampling, subset simulation, cross-entropy methods, extreme value/tail modeling, yield estimation.
Surrogate modeling and Uncertainty Quantification (a plus): Gaussian processes, polynomial chaos, sparse grids, variance reduction.

Applied Mathematics (any of the following is a plus)

Optimization: linear, nonlinear, convex, integer, stochastic, variational; robust/multi-objective; derivative-free/global methods (e.g., CMA-ES, Bayesian optimization).
Numerical analysis: numerical linear algebra (sparse/Krylov/preconditioning), stiff ODE/DAE solvers, approximation, quadrature; model reduction (POD/MOR).
Differential equations: ODE/PDE/SDE, dynamical systems.
Probability and statistics: stochastic processes, inference, uncertainty quantification.
Data science: statistical learning, optimization for ML, dimensionality reduction.

Familiarity with Machine Learning (preferred)

Classical ML: regression (linear/logistic), regularization (ridge/lasso), classification (SVM, kNN), ensembles (trees, random forests, boosting).
Contemporary AI (a plus): graph neural networks, transformers, reinforcement/transfer learning, representation learning, active learning.

Software and Systems (Not needed but any of the following is a plus)

Programming proficiency in Python and/or C++ is a plus (NumPy/SciPy, PyTorch/JAX, performance optimization, clean APIs).
Strong computer science background is a plus (data structures, algorithms, version control, testing, CI/CD).
HPC/parallel computing (a plus): MPI, CUDA, distributed workflows.

Any prior Experience in the following areas is a plus

Scientific computing in one or more areas: computational electromagnetics, fluid/thermal/molecular dynamics, computational physics, or electrical circuit simulation.
Electronic design automation (EDA): SPICE/Spectre/Verilog-A, netlists, PVT/Monte Carlo flows, yield/parametric corners.

Responsibilities

Research, design, and validate algorithms for circuit simulation, rare-event estimation, and optimization.
Quantify accuracy/speed vs. baselines; perform rigorous statistical analyses.
Build robust, maintainable implementations and integrate with production toolchains.
Good Team Player as well as collaborate with cross-functional teams and document methods and results clearly.

The annual salary range for California is $136,500 to $253,500. You may also be eligible to receive incentive compensation: bonus, equity, and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the salary range is a guideline and compensation may vary based on factors such as qualifications, skill level, competencies and work location. Our benefits programs include: paid vacation and paid holidays, 401(k) plan with employer match, employee stock purchase plan, a variety of medical, dental and vision plan options, and more.
We're doing work that matters. Help us solve what others can't.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: CADENCE
Position Id: cf7ba5c3ff480718d8f9b5cfbda53db9
Posted 30+ days ago

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