Role 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.
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.
Basic 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.
- 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.
About the company
Keysight’s AI Labs is a global R&D group pioneering the integration of machine learning, generative AIinto 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.