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Distributed Systems Engineer

Cadence

Distributed Systems Engineer

Cadence

Port Moody 01 (Vancouver)

·

On-site

·

Full-time

·

1mo ago

Required skills

Python

AWS

Go

GCP

Azure

Spark

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 Port Moody (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.

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About Cadence

Cadence

Cadence

Public

Cadence Design Systems provides electronic design automation (EDA) software, hardware, and IP for designing and verifying electronic systems and semiconductors.

5,001-10,000

Employees

San Jose

Headquarters

$8.5B

Valuation

Reviews

3.3

7 reviews

Work-life balance

2.0

Compensation

2.5

Culture

1.8

Career

2.0

Management

1.5

15%

Recommend to a friend

Pros

Built strong client relationships

Useful for repetitive tasks

Employment opportunities

Cons

Poor management and micromanagement

Lack of career growth opportunities

Technical architecture and code quality issues

Salary Ranges

65 data points

Junior/L3

Junior/L3 · Data Analyst

1 reports

$91,103

total per year

Base

$85,276

Stock

-

Bonus

$5,827

$59,612

$139,984

Interview experience

1 interviews

Difficulty

3.0

/ 5

Duration

14-28 weeks

Interview process

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Onsite/Virtual Interviews

5

Final Decision

Common questions

Technical Knowledge

Behavioral/STAR

Past Experience

Problem Solving