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 BuildArchitect 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
- 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
- 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)
- Experience with large-scale scientific/engineering visualization systems
- 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
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.Skills Required
- 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
- 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)
Cadence Design Systems Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Cadence Design Systems and has not been reviewed or approved by Cadence Design Systems.
-
Equity Value & Accessibility — A discounted ESPP with a lookback feature and equity included in total compensation make ownership broadly accessible and potentially meaningful. Structured compensation at an industry leader adds predictability to equity participation.
-
Healthcare Strength — Medical, dental, and vision coverage are described as solid, with mental‑health/EAP and fertility support enhancing the offering. The breadth across core care and family‑building needs strengthens the healthcare package.
-
Leave & Time Off Breadth — Global Recharge Days, volunteer time off, and companywide breaks indicate a comprehensive time‑off framework. In addition, many salaried roles are described as having flexible or generous PTO policies.
Cadence Design Systems Insights
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.
.jpeg)
