$150,000 - $350,000 USD yearly
Deploy machine learning systems directly into chip design environments using EDA tools, Linux, and Python.
Originally posted 4 November 2026 by the employer.
About the role
As a Software Engineer, ML for EDA, you will build the production software systems that integrate machine learning research into the ChipAgents platform and customer design environments. The work focuses on integrating with EDA tools, data pipelines, and compute infrastructure to address power, performance, and area problems in chip design.
What you'll do
- Build and maintain production software that operationalizes machine learning research within the ChipAgents platform.
- Integrate systems with EDA tools, flow scripts, libraries, and compute infrastructure across varied design environments.
- Construct data pipelines and tooling to transform EDA tool runs into datasets for model training and evaluation.
- Deploy and support software across customer environments, including on-premises and restricted-network setups.
- Develop reusable deployment tooling, adapters, and documentation from integration workflows.
- Maintain the reliability and performance of production services, incorporating customer feedback into research and engineering roadmaps.
What you'll need
- Strong software engineering skills in Python with experience developing production systems in Linux environments.
- Familiarity with the digital design flow, including synthesis, place and route, as well as timing and power analysis, along with the EDA tools used to run it.
- Working knowledge of machine learning methodologies, including how ML systems are trained, evaluated, and deployed.
- Experience deploying software into customer or enterprise environments, including compute farms (LSF, Slurm), containers, and restricted networks.
- Experience working directly with customer engineering teams and research counterparts to resolve technical issues.
Nice to have
- Hands-on experience with commercial EDA tools, including Tcl scripting.
- Experience as an engineer at an EDA vendor or semiconductor company.
- Familiarity with EDA data formats such as Verilog, Liberty, LEF/DEF, SDC, and SPEF.
- Experience with open-source EDA tools.
- Experience with LLMs or agent systems.
- MLOps experience with model packaging, versioning, and monitoring.
Skills: EDA tools, machine learning, Python, synthesis, place and route, Tcl
More semiconductor jobs: EDA tools engineer jobs
This role has been open 0 days — well below the 26-day median for EDA/CAD Engineering roles.
EDA/CAD Engineering · AI EDA Design
|
Open roles in category
90
|
Median days open
26 d
|
Category median salary (all employers)
$209k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | ChipAgents | All employers we track in this specialty (90 roles · 27 employers) |
|---|---|---|
| Open roles in this specialty | 6 | 90 |
| Open roles in the wider Physical Implementation family | 7 | 1585 · 117 employers |
| Median days open | 5 d | 26 d (−21 d vs this employer) |
| Median salary (USD postings) | — | $209k |
Skills observed across this category: EDA tools, machine learning, Python, synthesis, place and route, Tcl
Who's hiring in this category
- NVIDIA · 12 open roles · median 38 d
- NXP Semiconductors · 10 open roles · median 93 d
- Keysight Technologies · 8 open roles · median 35 d
- Cadence Design Systems · 6 open roles · median 69 d
- Qualcomm · 6 open roles · median 9 d
- Synopsys · 6 open roles · median 13 d
How we counted: 90 open EDA/CAD Engineering (AI EDA Design) roles from 27 employers tracked in the SemiconductorJobs index, counted 4 Nov 2026. Specialty figures count only roles carrying this exact specialty label, so an employer's related work in neighbouring specialties is not included there — it is counted in the wider Physical Implementation family row. Figures refresh nightly.