AI/CAD Software Engineer
Quick Summary
End-to-End ML Pipeline Development: Architect and maintain robust code for training and serving ML models that predict and optimize RF performance metrics.
Advanced scripting, object-oriented programming, and automation skills. ML Framework Expertise: Experience building models using PyTorch, TensorFlow, or scikit-learn.
Are you passionate about applying machine learning to transform the future of RF hardware? At Falcomm, we are revolutionizing wireless communications by integrating AI-driven solutions into the design of our energy-efficient Power Amplifier (PA) products. We are seeking a full-time AI/CAD Software Engineer to join our team. You will lead the development of intelligent tools that enhance RF workflows, automate complex EM simulations, and accelerate the tape-out of high-performance PAs. This role sits at the intersection of software engineering, machine learning, and RF physics, perfect for a developer who wants to get close to the hardware.
Responsibilities
~1 min read- →End-to-End ML Pipeline Development: Architect and maintain robust code for training and serving ML models that predict and optimize RF performance metrics.
- →PA Design Automation: Automate the creation and management of large-scale datasets derived from PA load-pull and electromagnetic (EM) simulations.
- →Tool Integration: Seamlessly integrate ML inference engines into existing RF EDA infrastructure to provide real-time feedback to PA designers.
- →Software Engineering Excellence: Establish best practices including comprehensive testing, CI/CD pipelines, and code reviews within an agile hardware team.
- →Cross-Functional Collaboration: Partner closely with RF/PA architects to translate complex impedance matching and linearity requirements into deployable software solutions.
Requirements
~1 min read- Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field.
- 2+ years of professional experience in software engineering or machine learning.
- Proficiency in Python: Advanced scripting, object-oriented programming, and automation skills.
- ML Framework Expertise: Experience building models using PyTorch, TensorFlow, or scikit-learn.
- Data Engineering: Strong grasp of data processing libraries (pandas, numpy, scipy) and file I/O operations.
- Software Fundamentals: Solid understanding of algorithms, data structures, and version control (Git).
- RF Domain Knowledge: RF front-end architectures, or a strong understanding of RF metrics (PAE, Gain, ACLR, EVM).
Nice to Have
~1 min read- RF PA Domain Knowledge: Experience with Power Amplifier design and an understanding of RF PA metrics.
- RF/EM Simulation Tools: Hands-on experience with Cadence Virtuoso, Ansys HFSS, or Keysight ADS.
- Open Source Innovation: Experience utilizing or contributing to open-source RF/EDA alternatives (e.g., gdsfactory, KLayout, Qucs, openEMS).
- Simulation Scripting: Familiarity with automating RF simulations via SKILL, AEL, or Python APIs.
- Physics-Informed ML: Interest or experience in applying ML to physics-based problems or electromagnetic modeling.
What We Offer
~1 min readLocation & Eligibility
Listing Details
- Posted
- February 5, 2026
- First seen
- September 28, 2026
- Last seen
- October 12, 2026
Posting Health
- Days active
- 13
- Repost count
- 0
- Trust Level
- 23%
- Scored at
- October 12, 2026
Signal breakdown
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