Senior Applied ML Engineer – Physics-Driven Systems & Optimization

Jordan martorell s.l.; Barcelona; Presencial; EUR 60.000 - 90.000; Jornada completa

Descripción de la vacante

A leading technology company in Barcelona is seeking a Senior Applied Machine Learning Engineer to design and implement state-of-the-art ML architectures. The role involves collaborating with experts to develop scalable ML systems and contribute to innovative solutions in various domains. Ideal candidates should have a Master’s or PhD in a relevant field along with strong experience in modern ML techniques and programming skills in Python, C++, and CUDA.

Formación

• 5+ years of experience applying scientific computing and optimization to real-world problems.
• Strong hands-on experience with modern ML architectures.
• Practical experience with generative models.

Responsabilidades

• Partner with Keysight experts to translate design workflows into ML-ready formulations.
• Design and implement advanced ML architectures.
• Develop scalable training and inference pipelines.

Conocimientos

Graph Neural Networks (GNNs)

Transformers

Reinforcement Learning

Generative Models

Educación

Master’s or PhD in Applied Mathematics, Scientific Computing, Computer Science, Electrical Engineering

Herramientas

Python

C++

CUDA

Descripción del empleo

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

Our 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

Join , 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.

About the AI Team

We 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.

About the Role

As 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.

Responsibilities

• Partner with Keysight experts in RF, EM, circuit, and measurement domains to translate physical constraints and design workflows into ML-ready formulations.
• Design and implement advanced ML architectures:
• Graph Neural Networks (GNNs) for geometry/topology-aware modeling
• Transformers for sequential and multimodal data
• Vision Models (CNNs, ViTs) for field- or spectrogram-based detection
• Generative Models (GANs, Diffusion) for data augmentation and design candidate generation
• Apply advanced optimization and control methods:
• Bayesian, gradient-based, and gradient-free optimization
• Reinforcement Learning (PPO, DDPG, SAC) for continuous tuning and control tasks
• Develop scalable training and inference pipelines (multi-GPU, HPC, AWS) ensuring efficiency and reliability.
• Write production-ready code in Python, C++, and CUDA , integrating with CI/CD pipelines and performance profiling tools.
• Benchmark ML and RL models against physics simulators and measurement datasets for robustness and reproducibility.
• Collaborate with product teams to embed AI/ML-based optimization and generative modules into Keysight software.
• Stay current with the latest ML, RL, and generative AI research; evaluate and prototype promising new techniques.

Required Qualifications

• Master’s or PhD in Applied Mathematics, Scientific Computing, Computer Science, Electrical Engineering , or related field
• 5+ years of experience applying scientific computing and optimization to real-world problems (e. g. , RF, EM, or measurement systems)
• Strong hands-on experience with modern ML architectures (GNNs, Transformers, Vision Models, Neural Operators)
• Practical experience with generative models (GANs, VAEs, Diffusion)
• Background in Bayesian and numerical optimization and hyperparameter tuning
• Applied experience with reinforcement learning (PPO, DDPG, SAC)
• Proficiency in Python, C++, CUDA , and GPU performance optimization
• Experience with multi-GPU/distributed training in HPC or cloud (Slurm, MPI, AWS)
• Excellent communication and collaboration skills across cross-functional teams

Desired Qualifications

• Experience applying ML/RL/generative models to parameter tuning, data augmentation, or design exploration
• Familiarity with Keysight simulation tools (ADS, RFPro, EMPro, Signal Studio, RaySim)
• Publications or patents in scientific ML, generative modeling, RL, or optimization
• Experience deploying ML/RL systems in production or embedded workflows

Keysight is an Equal Opportunity Employer.