Software Engineer – Fab Solutions R&D

Siemens EDA (Siemens Digital Industries Software); Santa Clara (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Siemens EDA (Siemens Digital Industries Software) is seeking a software engineer to design and implement software for Fab Solutions products, focusing on high-quality delivery across platforms.

The role requires a BS in a technical field and at least 2 years of professional experience in software engineering or data science using Python or C/C++. Proficiency in machine learning, computational geometry, and data-intensive manufacturing workflows is strongly preferred.

Qualifications

• BS in a technical field with 2+ years software engineering or data science experience.
• Experience with Python or C/C++ and data-intensive manufacturing workflows.
• Strong preference for ML, computational geometry and related skills.

Responsibilities

• Design and implement software for Fab Solutions products with high-quality delivery.
• Own full development lifecycle from concept and specification to testing and release validation.

Skills

Python

C/C++

Linux

Unix

Computational Geometry

Machine Learning

Statistical Modeling

Predictive Analytics

Scikit-learn

TensorFlow

Pandas

NumPy

Tcl/Tk

Shell Scripting

Data Pipelines

Algorithm Development

Education

Bachelor's degree in a technical field

Job description

The role involves designing and implementing software for Fab Solutions products, focusing on high-quality delivery and functional quality across platforms. Responsibilities include driving the full development lifecycle from conceptualization and specification to testing and release validation.

Requirements:

Requires a BS in a technical field with at least 2 years of professional experience in software engineering or data science using Python or C/C++. Proficiency in machine learning, computational geometry, and data-intensive manufacturing workflows is strongly preferred.

Key Skills:

• Python
• C/C++
• Linux
• Unix
• Computational Geometry
• Machine Learning
• Statistical Modeling
• Predictive Analytics
• Scikit-learn
• TensorFlow
• Pandas
• NumPy
• Tcl/Tk
• Shell Scripting
• Data Pipelines
• Algorithm Development