ML Intern – Calibration & Measurement Optimization
About The Position
Keysight is at the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. Our ~15,000 employees create world-class solutions in communications, 5G, automotive, energy, quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries. Learn more about what we do. Our award-winning culture embraces a bold vision of where technology can take us and a passion for tackling challenging problems with industry-first solutions. We believe that when people feel a sense of belonging, they can be more creative, innovative, and thrive at all points in their careers.
Requirements
- Pursuing PhD in EE (RF/Microwave), Applied Physics, CS, or related field.
- Hands-on RF measurement experience: S-parameter characterization, calibration, and de-embedding.
- Strong ML background with experience applying GNNs, Transformers, or Neural Operators to measurement or signal processing tasks.
- Background in Bayesian optimization applied to hardware calibration or measurement tuning.
- Familiarity with SCPI/IVI/PyVISA instrument control and RF measurement automation.
- Candidates who wish to be considered must be enrolled in a accredited college/university as of September 2026. Applicants who have graduated before September 2026 will not be considered unless they are entering/applying to a MS or PHD program after graduating.
- Visa Sponsorship is not available for this position. Candidates who now or at any point in the future require sponsorship for employment visa status (e.g., H-1B Visa status) may not be considered.
Nice To Haves
- Experience with advanced calibration techniques (multiline TRL, unknown thru, in-fixture, on-wafer probing).
- Background in load-pull, noise figure, or linearity characterization (IP3, P1dB) for RF device optimization.
- Familiarity with Keysight RF platforms (PNA, PNA-X, ENA) or simulation tools (ADS, RFPro).
- Publications or patents in ML for RF measurement, smart calibration, or adaptive test.
Responsibilities
- Partner with RF measurement and post-silicon teams to translate calibration workflows, de-embedding challenges, and characterization requirements into ML-ready formulations.
- Develop ML models for adaptive calibration (SOLT, TRL, multiline TRL), intelligent de-embedding, and fixture characterization — including Transformers for frequency-domain signal analysis and Vision Models for calibration artifact identification.
- Apply Bayesian/GP optimization for adaptive calibration loop closure, impedance tuner control, and parametric yield optimization; RL (PPO, DDPG, SAC) for automated measurement sequencing and closed-loop RF tuning.
- Build generative models for synthetic S-parameter dataset generation and calibration standard augmentation.
- Write production-ready Python (scikit-rf, PyTorch), C++, and CUDA code; integrate with instrument control frameworks (SCPI, IVI, VISA).
- Benchmark models against hardware measurements and physics-based calibration standards.
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What This Job Offers
Career Level
Intern
Education Level
Ph.D. or professional degree
