Cadence Design Systems Logo

Cadence Design Systems

Senior Distributed Systems Engineer - EDA/VLSI Platform

Reposted 8 Days Ago
Be an Early Applicant
In-Office
San Jose, CA, USA
154K-286K Annually
Senior level
In-Office
San Jose, CA, USA
154K-286K Annually
Senior level
Design and develop distributed data processing infrastructure for high-performance circuit simulation, focusing on data management, task orchestration, and visualization for massive circuit designs.
The summary above was generated by AI
At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology.

 About the Role                                                                                                                

We're building a next-generation distributed transistor-level electromigration and IR drop analysis tool. Our team has strong expertise in numerical solvers and circuit simulation algorithms. We need an experienced distributed systems engineer to design the scalable data processing infrastructure for handling massive circuit designs across distributed computing resources.                                          

What You'll Build                                                                                                                                                                                                                                                           

Architect and develop the core distributed infrastructure for a Python-based platform orchestrating high-performance C++ solvers, focusing on:                                                                                                                                                                    

Data Pipeline & I/O Management                                                                                                                                
  • Efficient ingestion pipelines for large-scale netlists and simulation data           
  • High-performance I/O for multi-TB circuit databases                                            
  • Serialization/deserialization layers bridging Python and C++ components          
  • Streaming results from distributed solver instances                                                                                                                                                                                               
Job Orchestration & Workflow                                                                                                                                        
  • Task distribution architecture with fault-tolerant scheduling for long-running simulations                                                                                 
  • Resource management and load balancing across compute clusters                  
  • Monitoring and observability for distributed workflows                                          
  • Optimization of task granularity and dependency management                                                                                                                                                                        
Visualization & Analytics                                                                                                                                                    
  •  Scalable visualization for multi-dimensional TB-scale simulation results            
  • Interactive data exploration and optimization techniques (downsampling, LOD, progressive rendering)                                                                        

                                                                                                                                             

Required Expertise                                                                                                                                                                                                                                                           Distributed Systems                                                                                                                                                          
  • 5+ years building production distributed systems with Python                              
  • Deep experience with Dask Distributed or similar frameworks (Spark, Ray, Celery)                                                                                           
  • Strong grasp of distributed computing patterns, data locality, and fault tolerance                                                                                         

                                                                                                                                             

Data Engineering                                                                                                                                                             
  • Expertise in high-performance I/O (HDF5, Parquet, Arrow, columnar formats)    
  • Data partitioning strategies, memory-mapped files, zero-copy techniques, streaming patterns                                                                                
  • Python/C++ interop (pybind11, Cython, ctypes)                                                                                                                                                                                                       
Big Data Visualization                                                                                                        
  • Experience with large-scale scientific/engineering visualization systems                                                                                                                                                          
Nice to Have                                                                                                                                                                                                                                 
  • Background in EDA, VLSI, semiconductor design, or computational engineering                                                                                                
  • HPC experience with job schedulers (Slurm, PBS, LSF)                                            
  • GPU acceleration knowledge 
  • Familiarity with modern languages, tools (Go, Plotly, Bokeh, Holoviews, Datashader)                                                                                                               
  • Open-source distributed computing contributions                                                                                                                                                                                                 
Why Join Us                                                                                                                                                                  

 We bring strong expertise in numerical methods and circuit analysis algorithms, well-defined solver interfaces, and a clear technical vision. You'll build greenfield distributed infrastructure with modern tools, designing the scalable foundation that makes advanced analysis capabilities accessible to chip design engineers.               

                                                                                                                                                                               

Ideal Candidate                                                                                                                                                              

You're a systems thinker excited about data pipeline architecture and production-scale distributed systems. You understand orchestrating heterogeneous workloads and designing elegant abstractions for distributed computing. You prioritize observability, fault tolerance, and user experience alongside performance.

No circuit simulation expertise needed—that's our strength. We need your expertise building scalable, reliable infrastructure.                                               

The annual salary range for California is $154,000 to $286,000. 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.
HQ

Cadence Design Systems San Jose, California, USA Office

2655 Seely Avenue, San Jose, CA, United States, 95134

Similar Jobs

32 Minutes Ago
Hybrid
San Jose, CA, USA
209K-286K Annually
Senior level
209K-286K Annually
Senior level
Fintech • Machine Learning • Payments • Software • Financial Services
Lead a portfolio of technology projects with a team of developers to create solutions for regulatory needs, collaborating on cloud-based projects while mentoring engineers.
Top Skills: Amazon SagemakerAWSCSSDatabricksDockerGoHTMLJavaJavaScriptKubernetesLuaMcpPythonSQLTypescript
110K-125K Annually
Junior
Fintech • Machine Learning • Payments • Software • Financial Services
The Dealer Success Manager collaborates with sales teams to implement sales strategies and drive adoption of the Navigator Platform, ensuring customer satisfaction and retention. Responsibilities include relationship management, process improvement, and market visits to auto dealerships.
Top Skills: Navigator PlatformVarious Sales Tools
32 Minutes Ago
Hybrid
2 Locations
197K-246K Annually
Mid level
197K-246K Annually
Mid level
Fintech • Machine Learning • Payments • Software • Financial Services
Lead the design, development, and deployment of AI software components while partnering with engineers and scientists to deliver innovative AI solutions at Capital One.
Top Skills: AWSAzureGoGCPHuggingfaceJavaNemo GuardrailsPythonPyTorchScalaVectordbs

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account