# R&D Engineering, Engineer

**Company**: Synopsys
**Location**: Hsinchu, Taiwan
**Work arrangement**: onsite
**Experience**: mid
**Job type**: full-time
**Category**: Engineering
**Industry**: Technology
**Ticker**: SNPS
**Wikidata**: https://www.wikidata.org/wiki/Q2303478

**Apply**: https://careers.synopsys.com/job/hsinchu/r-and-d-engineering-engineer/44408/100607370512?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_848e3a56-52b

## Description

Synopsys software engineers are key enablers in the world of Electronic Design Automation (EDA), developing and maintaining software used in chip design, verification and manufacturing.

You are a passionate software engineer with a strong background in algorithms and system-level thinking. You enjoy solving complex problems and are driven to build scalable and efficient backend solutions for large-scale hardware systems.

**Responsibilities**

- Develop and optimize multi-FPGA partitioning algorithms for the ZeBu emulation compile flow, going beyond pure cut-size minimization

- Build timing-aware partitioning solutions that incorporate critical path timing criticality into partition cost models and optimization objectives

- Account for ZeBu clocking constraints,such as driver-clock-driven user clocks via multi-cycle paths,when evaluating partition quality and feasibility

- Design and enhance a more robust partitioning engine that reduces sensitivity to random initial solutions in traditional hMetis-based flows

- Apply analytical partitioning approaches to improve initial solution quality, stability, and reproducibility

- Work on constraint-aware partitioning for logic/memory resources, inter-FPGA connectivity, and timing-related partition constraints

- Collaborate closely with the FPGA P&R and runtime teams to validate partitioning decisions and support ZeBu platform sign-off

- Analyze partitioning bottlenecks and implement scalable, maintainable C/C++ backend components on Linux

**The Impact You Will Have**

- Improve emulation performance by making partitioning timing-aware, not just cut-size driven

- Increase partitioning robustness and reproducibility by reducing dependence on random initial solutions

- Improve partition quality and compile outcomes for large SoC designs through a more stable partitioning engine

- Enable successful ZeBu platform sign-off by delivering partitioning solutions validated with FPGA P&R and runtime teams

- Advance state-of-the-art emulation partitioning by combining classical graph partitioning with analytical optimization techniques

**Requirements**

- Bachelor’s or master’s degree in computer science, Electrical Engineering, or a related field

- Strong foundation in algorithms, data structures, and graph/hypergraph partitioning

- Experience with C/C++ and performance-oriented software development on Linux/Unix

- Knowledge of optimization techniques and partitioning algorithms (e.g., hMetis, multi-way partitioning, heuristic and analytical methods)

- Understanding of timing-aware optimization or willingness to develop expertise in timing-critical partitioning

**Benefits**

- Comprehensive medical and healthcare plans that work for you and your family

- Time away: ETO and FTO Programs

- Family support: maternity and paternity leave, parenting resources, adoption and surrogacy assistance, and more

- ESPP: purchase Synopsys common stock at a 15% discount, with a 24-month look-back

- Retirement plans: save for your future with our retirement plans that vary by region and country

- Competitive salaries

## Skills

### Required
- algorithms
- data structures
- graph/hypergraph partitioning
- C/C++
- performance-oriented software development
- Linux/Unix
- optimization techniques
- partitioning algorithms

### Nice to have
- clock synthesis
- multi-cycle path concepts
- analytical approaches to partitioning
- large-scale optimization

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Source: [Apply at careers.synopsys.com](https://careers.synopsys.com/job/hsinchu/r-and-d-engineering-engineer/44408/100607370512?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)