Senior Distributed Systems Engineer - EDA/VLSI Platform
About The Position
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)
Requirements
- 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 Haves
- 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
Responsibilities
- Architect and develop the core distributed infrastructure for a Python-based platform orchestrating high-performance C++ solvers
- 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)
Benefits
- paid vacation and paid holidays
- 401(k) plan with employer match
- employee stock purchase plan
- a variety of medical, dental and vision plan options
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
