Summary: Join Keysight's AI Labs as a Machine Learning Engineer to develop and productize advanced LLM-based, agentic, and generative AI pipelines, blending research, engineering, and productization. Highlights: 1. Pioneering integration of machine learning and generative AI into solutions 2. Develop and productize advanced LLM-based, agentic, and generative AI pipelines 3. Work with cutting-edge ML concepts into deployable real-world solutions Overview: Keysight 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. 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. **About Keysight AI Labs** Keysight’s **AI Labs** is a global R\&D 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. **About the AI Team****Join** ***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. **About the Role** We are looking for a **Machine Learning Engineer** (senior level preferred) to develop and productize advanced **LLM\-based, agentic, and generative AI pipelines**. You’ll design scalable architectures that integrate AI into Keysight’s software and hardware platforms, enabling intelligent workflows, root\-cause analysis, automated scripting, anomaly detection, and adaptive decision\-making. This role blends **research, engineering, and applied productization**, ideal for those who enjoy turning cutting\-edge ML concepts into deployable real\-world solutions. Responsibilities: * Collaborate with Keysight domain experts (RF, 6G\-wireless, EM, circuit, and measurement) to gather requirements, physical constraints, and workflow insights for ML pipeline design. * Design and implement **SOTA ML architectures** including LLMs, agentic systems, GANs, diffusion models, and RAG pipelines for data augmentation, anomaly detection, modeling, and automation. * Develop scalable ML pipelines for **on\-device, on\-prem, cloud, and hybrid GPU environments**, ensuring efficiency, reliability, and scalability. * Write **production\-grade Python, C\+\+, and CUDA** code following best practices (testing, CI/CD, documentation, performance profiling). * Collaborate with product teams to integrate ML\-driven features into Keysight’s commercial products. * Continuously explore and apply **new research** in LLMs, agentic reasoning, multimodal AI, and generative architectures to enhance Keysight’s capabilities. Qualifications: **Required Qualifications*** **Education:** Master’s or PhD in Computer Science, Electrical Engineering, Applied Mathematics, or a related field. * **Strong ML/DL foundations:** solid understanding of neural architectures, optimization, and evaluation metrics. * **Hands\-on experience** with PyTorch (preferred) or TensorFlow. * Proven expertise building or fine\-tuning **transformer architectures (GPT, T5, LLaMA, etc.)**. * Experience with **LLM fine\-tuning, instruction tuning, RLHF, PPO/DPO**, or similar adaptation techniques. * Strong coding skills in **Python** and familiarity with **CI/CD, testing, Git versioning, and containerization (Docker/Kubernetes)**. * Experience with **data pipelines** (tokenization, preprocessing, large text corpora). * Experience with **MLOps tools** (MLflow, Weights \& Biases, Ray). * Experience with **agentic workflows**, RAG systems, or multimodal (text, code, signal) applications. * Excellent communication and teamwork skills; comfortable working in cross\-functional R\&D environments. **Desired Qualifications*** Familiarity with **cloud environments** (Azure, AWS, or GCP). * Experience optimizing models for **edge or embedded environments**. * Knowledge of **model compression, quantization, or inference optimization**. * Research literacy and the ability to **read, reproduce, and extend SOTA papers**. * Open\-source contributions or public ML repositories are a strong plus. * Prior experience with Keysight software, test and measurement workflows, or domain\-specific modeling is highly valued. Careers Privacy Statement\*\*\*Keysight is an Equal Opportunity Employer.\*\*\*