ppJoin to apply for the bSr Applied ML Engineer – Physics-Driven Systems Optimization /b role at bKeysight Technologies /b /p h3Overview /h3 pKeysight is on 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. /p h3About Keysight AI Labs /h3 pKeysight’s AI Labs is a integral RD group pioneering the integration of machine learning, generative AI into Keysight’s test, measurement, and design solutions. Our mission is to transform how engineers design, simulate, and validate advanced systems—from 6G and semiconductors to quantum and automotive—by embedding AI throughout our workflows. /p h3About The AI Team /h3 pJoin Keysight's central AI Hub in the heart of Barcelona. We are expanding our newly formed AI Team. As part of this growing team, you will join a vibrant, cross‑functional environment that brings together experts in ML engineering, data science, physics‑informed modeling, and software development. You’ll work closely with domain experts across RF, EM, circuit design, and test measurement to accelerate scientific innovation through AI. /p h3About The Role /h3 pAs a Senior Applied Machine Learning Engineer, you will design, implement, and deploy state‑of‑the‑art ML architectures that merge physics insights, numerical optimization, and modern AI techniques. You’ll contribute to building scalable and explainable ML systems, from geometry‑aware GNNs and Transformers to reinforcement learning and generative models, that drive design automation,



anomaly detection, and optimization in Keysight’s next‑generation platforms. /p h3Responsibilities /h3 ul liPartner with Keysight experts in RF, EM, circuit, and measurement domains to translate physical constraints and design workflows into ML‑ready formulations. /li liDesign and implement advanced ML architectures: ul liGraph Neural Networks (GNNs) for geometry/topology‑aware modeling /li liTransformers for sequential and multimodal data /li liVision Models (CNNs, ViTs) for field‑ or spectrogram‑based detection /li liGenerative Models (GANs, Diffusion) for data augmentation and design candidate generation /li /ul /li liApply advanced optimization and control methods: ul liBayesian, gradient‑based, and gradient‑free optimization /li liReinforcement Learning (PPO, DDPG, SAC) for continuous tuning and control tasks /li /ul /li liDevelop scalable training and inference pipelines (multi‑GPU, HPC, AWS) ensuring efficiency and reliability. /li liWrite production‑ready code in Python, C++, and CUDA, integrating with CI/CD pipelines and performance profiling tools. /li liBenchmark ML and RL models against physics simulators and measurement datasets for robustness and reproducibility. /li liCollaborate with product teams to embed AI/ML‑based optimization and generative modules into Keysight software. /li liStay current with the latest ML, RL,



and generative AI research; evaluate and prototype promising new techniques. /li /ul h3Qualifications /h3 h3Required Qualifications /h3 ul liMaster’s or PhD in Applied Mathematics, Scientific Computing, Computer Science, Electrical Engineering, or related field /li li5+ years of experience applying scientific computing and optimization to real‑world problems (e.g., RF, EM, or measurement systems) /li liStrong hands‑on experience with modern ML architectures (GNNs, Transformers, Vision Models, Neural Operators) /li liPractical experience with generative models (GANs, VAEs, Diffusion) /li liBackground in Bayesian and numerical optimization and hyperparameter tuning /li liApplied experience with reinforcement learning (PPO, DDPG, SAC) /li liProficiency in Python, C++, CUDA, and GPU performance optimization /li liExperience with multi‑GPU/distributed training in HPC or cloud (Slurm, MPI, AWS) /li liSolid software‑engineering discipline (testing, CI/CD, modular design) /li liExcellent communication and collaboration skills across cross‑functional teams /li /ul h3Desired Qualifications /h3 ul liExperience applying ML/RL/generative models to parameter tuning, data augmentation, or design exploration /li liFamiliarity with Keysight simulation tools (ADS, RFPro, EMPro, Signal Studio, RaySim) /li liPublications or patents in scientific ML, generative modeling, RL, or optimization /li liExperience deploying ML/RL systems in production or embedded workflows /li /ul pKeysight is an Equal Opportunity Employer. /p pSeniority level: Not Applicable /p pEmployment type: Full‑time /p pJob function: Engineering and Information Technology /p pIndustries: Appliances, Electrical, and Electronics Manufacturing /p /p #J-18808-Ljbffr

📌 Sr Applied ML Engineer – Physics-Driven Systems & Optimization (Barcelona)
🏢 Keysight Technologies
📍 Barcelona