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 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 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 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 greenfield distributed infrastructure with modern tools. This is an opportunity to grow your expertise in production-scale distributed systems while solving challenging problems in chip design. What You'll Learn * Production distributed systems architecture and patterns * Large-scale data pipeline design and optimization * Performance engineering for multi-TB datasets * Building reliable, observable infrastructure * Working with domain experts in circuit simulation and numerical methods Ideal Candidate You're eager to deepen your distributed systems expertise and excited about data pipeline architecture. You have foundational experience with Python distributed computing and want to tackle production-scale challenges. You're comfortable learning new technologies, asking questions, and collaborating with both systems and domain experts. You value clean code, observability, and user experience alongside performance. No circuit simulation expertise needed. We need your enthusiasm for building scalable, reliable infrastructure and your willingness to grow into a distributed systems expert. Position Location * This is a full-time, on-site position based in Burnaby (Greater Vancouver Area) Canada. In-office attendance is required. The annual salary range for British Columbia is 89,600 CAD to 166,400 CAD. 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 holidays, leave of absence programs, Registered Retirement Savings Plan (RRSP), Tax Free Savings (TFSA) plan for post-tax investment savings, Employee Stock Purchase Plan, group health coverage that includes dental, vision and Emotional Wellbeing Support (EAP) benefits for you and your eligible dependents. Cadence also offers employee and dependent Life insurance, and short-term and long-term disability. In addition, Cadence provides Global Travel Medical coverage, Business Travel Accident Insurance, and a funded Lifestyle Spending Account (LSA). WE’RE DOING WORK THAT MATTERS. HELP US SOLVE WHAT OTHERS CAN’T.

Build scalable data processing infrastructure and ingestion pipelines for massive circuit designs using a Python-based platform. Implement task distribution, fault-tolerant scheduling, and high-performance I/O for distributed solver results.

Requires 3+ years of experience building distributed systems with Python and familiarity with frameworks like Dask, Spark, or Ray. Candidates should have experience with high-performance data formats and production-level software engineering practices.

• Paid Vacation • Paid Holidays • Leave Of Absence Programs • Registered Retirement Savings Plan (RRSP) • Tax Free Savings (TFSA) Plan • Employee Stock Purchase Plan • Group Health Coverage • Dental Insurance • Vision Insurance • Emotional Wellbeing Support (EAP) • Life Insurance • Short-term Disability • Long-term Disability • Global Travel Medical Coverage • Business Travel Accident Insurance • Lifestyle Spending Account (LSA)

• C++Preferred
• PythonPreferred

Identified from the job description. Confirm important requirements above.

• Python
• Distributed Systems
• C++
• Dask
• Spark
• Ray
• Celery
• HDF5
• Parquet
• Arrow
• Pybind11
• Nanobind
• Data Pipelines
• Fault-tolerant Scheduling
• Load Balancing
• Resource Management

• Software
• Technology
• Engineering
• Data & Analytics
• Science & Research

Minimum experience

3+ years

Posting language

English

Working hours

40 hours per week