ppKeysight 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 pOur 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. /p h3About Keysight AI Labs /h3 pJoin Keysight's central AI team in Barcelona, a newly formed hub driving innovation in machine learning. As part of this growing team, you’ll have the chance to shape our AI strategy and make an immediate impact. Our work spans supervised and unsupervised learning, generative models, multimodal systems, reinforcement learning, and large language models. /p h3About the AI Team /h3 pWe are expanding the Team and You’ll join a cross-disciplinary AI Modeling team in the heart of Barcelona. The Team develops physics-informed, data-driven, and reinforcement learning systems that accelerate design, measurement, and optimization processes across domains such as RF, EM, circuits, and advanced instrumentation. The group collaborates closely with hardware engineers, domain scientists, and product software developers to bring AI models from research into production tools used globally. /p h3About the Role /h3 pAs a bSenior Deep Learning Engineer /b, you will design, build, and deploy advanced deep learning models and scalable ML systems that power real‑world applications.



/p pYou will contribute across the full ML lifecycle — from research and experimentation to large-scale training and production deployment — ensuring high standards in performance, reliability, and maintainability. /p pThis role requires strong hands‑on experience with modern deep learning architectures and distributed training techniques, as well as the ability to translate research concepts into efficient, production-ready implementations. /p h3Responsibilities /h3 ul liDesign and implement advanced deep learning architectures, including: ul liTransformer‑based models /li liSequence and representation learning models /li liPrediction, classification, and representation learning tasks /li liGenerative modeling approaches (diffusion models, autoregressive models, VAEs) /li /ul /li liBuild and optimize scalable training pipelines: ul liDistributed training using DDP, FSDP, DeepSpeed or similar frameworks /li liMulti‑GPU and multi‑node training environments /li /ul /li liImprove model efficiency and performance: ul liMemory optimization techniques /li liGPU utilization profiling and optimization /li /ul /li liDevelop production‑ready ML systems: ul liModel serving and inference optimization /li liDeployment pipelines and integration into production environments /li liMonitoring, validation, and performance tracking /li /ul /li liContribute to engineering excellence: ul liWrite high‑quality, maintainable,



and well‑tested code /li liApply best practices in modular design, testing, and CI/CD /li liParticipate in design reviews and architecture discussions /li /ul /li liStay current with advances in deep learning and evaluate new methods for practical applicability. /li /ul h3Required Qualifications /h3 ul liMaster’s or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field /li li5+ years of hands‑on experience developing deep learning or machine learning systems in production or research environments /li liStrong experience with modern deep learning frameworks /li liStrong understanding of deep learning fundamentals: ul liOptimization techniques and training dynamics /li /ul /li liExperience training models at scale: ul liMulti‑GPU or multi‑node distributed environments /li /ul /li liExperience with C++ and/or CUDA is a plus /li liExperience optimizing model performance and training efficiency /li liSolid software engineering practices: ul liTesting and CI/CD pipeline /li liModular and maintainable code design /li /ul /li liStrong collaboration and communication skills in cross‑functional environments /li /ul h3Desired Qualifications /h3 ul liExperience training or deploying large‑scale foundation models or generative models /li liExperience with model optimization techniques: ul liDistillation /li /ul /li liExperience working with distributed compute environments or HPC clusters /li liContributions to open‑source ML projects, publications, or technical communities /li liExperience working in interdisciplinary environments involving scientific or engineering data /li /ul pCareers Privacy Statement: Keysight is an Equal Opportunity Employer. /p /p #J-18808-Ljbffr

📌 Senior Deep Learning Engineer (PyTorch, Distributed Training) (Barcelona)
🏢 Keysight Technologies
📍 Barcelona