Distributed Systems Engineer

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're looking for a motivated distributed systems engineer to help build the scalable data processing infrastructure for handling massive circuit designs across distributed computing resources. What You'll Build You'll contribute to the core distributed infrastructure for a Python-based platform orchestrating high-performance C++ solvers, working on:   Data Pipeline & I/O Management   Build ingestion pipelines for large-scale netlists and simulation data   Implement high-performance I/O for multi-TB circuit databases   Develop serialization/deserialization layers bridging Python and C++ components   Design streaming interfaces for distributed solver results   Job Orchestration & Workflow   Implement task distribution with fault-tolerant scheduling for long-running simulations   Develop resource management and load balancing across compute clusters   Build monitoring and observability for distributed workflows   Optimize task granularity and dependency management   Visualization & Analytics   Develop scalable visualization for multi-dimensional TB-scale simulation results   Implement interactive data exploration with optimization techniques (downsampling, LOD, progressive rendering) Required Expertise   Distributed Systems   3+ years building distributed systems with Python   Experience with distributed computing frameworks (Dask, Spark, Ray, or Celery)   Understanding of distributed computing patterns, data locality, and fault tolerance   Data Engineering   Experience with high-performance data formats (HDF5, Parquet, Arrow, or similar columnar formats)   Familiarity with data partitioning strategies and streaming patterns   Some exposure to Python/C++ interop (pybind11, nanobind)   Software Engineering   Strong Python, C++ programming skills with production code experience   Comfortable working in large codebases and collaborative development environments   Understanding of software engineering best practices (testing, code review)   Nice to Have   Background in EDA, VLSI, semiconductor design, or computational engineering   Experience with scientific/engineering data visualization   HPC experience with job schedulers (Slurm, PBS, LSF)   GPU acceleration knowledge   Familiarity with modern tools (Go, Plotly, Bokeh, Holoviews, Datashader)   Open-source distributed computing or other contributions   Experience with cloud platforms (AWS, GCP, Azure) 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 work alongside experienced engineers building…