Senior Machine Learning Engineer – LLMs & Agentic AI

Overview

About Keysight AI Labs

Keysight accelerates innovation to connect and secure the world. Our solutions span wireless communications, semiconductors, aerospace & defense, automotive, and beyond. We combine measurement science, simulation, and advanced AI to help engineers design, simulate, and validate the world’s most advanced systems.

About the AI Team 

Keysight’s AI Labs is a global R&D group pioneering the integration of machine learning, generative AI, and agentic systems 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.

The Barcelona AI hub is 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).
• Familiarity with cloud environments (Azure, AWS, or GCP).
• Excellent communication and teamwork skills; comfortable working in cross-functional R&D environments.

Desired Qualifications

• Familiarity with agentic workflows, RAG systems, or multimodal (text, code, signal) applications.
• 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.