AI Platform Engineer

Keysight Technologies; Barcelona; Sur place; EUR 70 000 - 110 000; Plein temps

Résumé du poste

Keysight is seeking an AI Platform Engineer to join our data and IP management product team to build the SOS AI platform and the MLOps infrastructure powering the AI lifecycle.

You will design, build, and operate the platform on-premises, implement reproducible workflows, ensure traceability, and collaborate with ML engineers and customers to deliver durable platform capabilities.

Qualifications

• 5+ years building and operating AI or data platforms in production.
• Hands-on experience with Prefect, Airflow, or Dagster.
• Strong containerization and orchestration with Docker and Kubernetes.
• Solid Python backend engineering, API design, and PostgreSQL usage.
• Experience with ML tooling (MLflow) and messaging systems (Kafka or NATS).
• Experience delivering on-premises or air-gapped systems.

Responsabilités

• Design, build, and operate the SOS AI platform and its MLOps infrastructure for the AI lifecycle on-premises.
• Build experiment orchestration as versioned, reproducible workflows with context and replay.
• Implement asset registries and end-to-end lineage for models, data, and results.
• Package and deploy the platform as a self-contained system for customer environments.
• Integrate the platform with engineering/EDA workflows to ensure clean data flow between tools.
• Own platform reliability and performance, including observability and upgrade paths.
• Establish access control, audit trails, and reproducibility guarantees for IP-sensitive data.
• Collaborate with ML engineers, product, and customers to translate needs into durable platform capabilities.

Connaissances

Workflow orchestration

Backend engineering

Python

API design

Distributed systems

Formation

BS/MS/PhD in CS or Engineering

Outils

Prefect

Airflow

Dagster

Docker

Kubernetes

Description du poste

Overview

We are looking for an Artificial Intelligence (AI) Platform Engineer to join our industry-leading data and IP management product team to build the Machine Learning Operations (MLOps) infrastructure that powers SOS AI, our AI lifecycle management platform that brings together Electronic Design Automation (EDA) and AI/ML workflows.

Keysight is at the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. Our ~16,800 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

• Design, build, and operate the SOS AI platform: the orchestration, tracking, messaging, and application services that run the AI/ML lifecycle on-premises.
• Build experiment orchestration as versioned, reproducible workflows, with run context, task dependencies, execution tracking, and reliable replay.
• Implement asset registries and end-to-end lineage so every model, dataset, and result is traceable to the exact inputs, parameters, and workflow version that produced it.
• Package and deploy the platform as a self-contained system that runs reliably in customer environments without dependence on external services.
• Integrate the platform with engineering and EDA workflows so that data flows cleanly between tools and the experiment substrate.
• Own platform reliability and performance: observability, scaling, upgrade paths, and operational tooling for the backend services.
• Establish access control, audit trails, and reproducibility guarantees appropriate for IP-sensitive engineering data.
• Collaborate with ML engineers, product, and customers to turn AI/ML workflow needs into durable platform capabilities.

Qualifications

• BS, MS, or Ph.D. in Computer Science, Engineering, or related field
• 5+ years building and operating AI or data platforms in production.
• Hands-on experience with workflow orchestration, particularly Prefect (or comparable orchestrators such as Airflow or Dagster).
• Strong containerization and orchestration skills (Docker and Kubernetes) for building and deploying distributed backend services.
• Solid backend engineering in Python, including API design, relational databases (PostgreSQL), and service architecture.
• Experience with MLOps tooling such as experiment tracking and model registries (for example MLflow), and with messaging or eventing systems (for example NATS or Kafka).
• Experience delivering on-premises or air-gapped systems, with a focus on reliability and operability.
• Experience with high-performance computing (HPC) environments and job schedulers is valued.
• Experience in semiconductor, EDA, or other engineering domains is a plus.

Careers Privacy Statement Keysight is an Equal Opportunity Employer.