Distributed Systems Engineer

Job Title

Distributed Systems Engineer

Role Summary

Join a small team building a next-generation distributed electromigration and IR drop analysis platform. The role focuses on designing and implementing scalable data pipelines, high-performance I/O, and orchestration for Python-based workflows that drive C++ simulation solvers.

The engineer will collaborate with numerical solver and circuit-simulation experts to build reliable, observable infrastructure for multi‑TB datasets and long‑running distributed simulations.

Experience Level

Mid-level. The posting requests 3+ years of experience building distributed systems with Python.

Responsibilities

Work on the core distributed infrastructure and data processing needed to run large-scale circuit simulations across compute clusters.

• Design and build ingestion pipelines for large netlists and simulation outputs.
• Implement high-performance I/O and storage strategies for multi‑TB circuit databases.
• Develop serialization/deserialization and Python/C++ interoperability layers.
• Design streaming interfaces for producing and consuming distributed solver results.
• Implement task distribution, fault-tolerant scheduling, and resource management for long-running jobs.
• Optimize task granularity, dependency management, and load balancing across clusters.
• Build monitoring, observability, and performance diagnostics for distributed workflows.

Requirements

Must-have technical experience and skills for immediate contribution.

• 3+ years building distributed systems using Python.
• Experience with distributed computing frameworks such as Dask, Spark, Ray, or Celery.
• Understanding of distributed computing patterns, data locality, and fault tolerance.
• Experience with high-performance data formats (HDF5, Parquet, Arrow or similar) and data partitioning/streaming strategies.
• Familiarity with Python/C++ interop (e.g. pybind11, nanobind) and production-grade Python development.
• Good software engineering practices: testing, code review, and working in large codebases.

Nice-to-have:

• Background in EDA, VLSI, semiconductor design, or computational engineering.
• HPC experience (job schedulers like Slurm/PBS/LSF), GPU acceleration, or cloud platforms (AWS/GCP/Azure).
• Experience with scientific visualization tools and modern languages/tools (Go, Plotly, Bokeh, Holoviews, Datashader).
• Contributions to open-source distributed computing projects.

Education Requirements

Not specified.

About the Company

Company: Cadence Design Systems

Headquarters: San Jose, California, USA

Cadence Design Systems is a global electronic design automation company that provides software, hardware, and intellectual property for designing advanced semiconductor chips. With over 25 years in the industry, Cadence is known for its innovative technology solutions and has been recognized by Fortune Magazine as one of the 100 Best Companies to Work For. The company is dedicated to solving complex technical challenges in order to enable customers to create revolutionary products and experiences.