Senior Distributed Systems Engineer - EDA/VLSI Platform

Reposted 15 Days Ago
Be an Early Applicant
San Jose, CA, USA
In-Office
154K-286K Annually
Senior level
Artificial Intelligence • Cloud • Hardware • Software • Semiconductor
The Role
Design and develop distributed data processing infrastructure for high-performance circuit simulation, focusing on data management, task orchestration, and visualization for massive circuit designs.
Summary Generated by Built In
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.

Top Skills

Arrow
C++
Celery
Dask
Hdf5
Parquet
Python
Ray
Spark
Am I A Good Fit?
beta
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.

The Company
HQ: San Jose, CA
8,216 Employees
Year Founded: 1988

What We Do

Cadence enables electronic systems and semiconductor companies to create the innovative end products that are transforming the way people live, work and play. Cadence® software, hardware and IP are used by customers to deliver products to market faster. The company's Intelligent System Design strategy helps customers develop differentiated products—from chips to boards to intelligent systems—in mobile, consumer, cloud, data center, automotive, aerospace, IoT, industrial and other market segments. Cadence is listed as one of Fortune Magazine's 100 Best Companies to Work For.

Similar Jobs

HopSkipDrive Logo HopSkipDrive

Senior Android Engineer

Automotive • Edtech • Kids + Family • Mobile • Social Impact • Transportation
Easy Apply
In-Office
Los Angeles, CA, USA
450 Employees
185K-185K Annually

Snap Inc. Logo Snap Inc.

Senior Manager, Client Partner

Artificial Intelligence • Cloud • Machine Learning • Mobile • Software • Virtual Reality • App development
Hybrid
3 Locations
5000 Employees
235K-414K Annually

Cox Enterprises Logo Cox Enterprises

Communications Specialist

Artificial Intelligence • Automotive • Greentech • Information Technology • Machine Learning • Software • Cybersecurity
Remote or Hybrid
United States
50000 Employees
50K-76K Annually

Verkada Inc Logo Verkada Inc

Engineering Manager

Cloud • Hardware • Security • Software
In-Office
San Mateo, CA, USA
2000 Employees
220K-315K Annually

Similar Companies Hiring

Fairly Even Thumbnail
Software • Sales • Robotics • Other • Hospitality • Hardware
New York, NY
Bellagent Thumbnail
Artificial Intelligence • Machine Learning • Business Intelligence • Generative AI
Chicago, IL
20 Employees
Kepler  Thumbnail
Fintech • Software
New York, New York
6 Employees

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account