Overview
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. The Keysight AI Labs is pioneering scientific machine learning and physics & T&M-informed AI to transform Keysight s software, simulation, and measurement products. We are looking for a versatile Software Developer who can operate both horizontally across multiple services. You ll play a key role in designing, building, and scaling services while contributing to infrastructure, backend, and frontend needs. The ideal candidate is flexible, thrives in dynamic environments, and can deliver high-quality solutions quickly.
Keysight is at 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
Key Responsibilities
- Design and implement MLOps pipelines for training, validation, deployment, and monitoring of machine learning models.
- Develop and maintain infrastructure for data versioning, model registries, and experiment tracking (e.g., MLflow, LakeFS, Airflow).
- Integrate orchestration tools (e.g., Kubeflow, Ray, Airflow) to support automated workflows and distributed training.
- Collaborate with data scientists and software engineers to ensure seamless model handoff and deployment.
- Build APIs and SDKs to abstract infrastructure complexity and enable self-service model development.
- Implement monitoring and alerting systems for model drift, performance degradation, and system health.
- Support on-prem and cloud-based deployments (e.g., Kubernetes, HPC clusters, AWS).
Qualifications
Required Qualifications
- Bachelor s or Master s degree in Computer Science, Software Engineering, or related field.
- 3+ years of experience in software development, preferably in AI/ML infrastructure or data platforms.
- Proficiency in Python and/or TypeScript/JavaScript.
- Experience with backend frameworks (e.g., FastAPI, Flask, Node.js) and frontend libraries (e.g., React, Vue).
- Familiarity with cloud services (AWS preferred), containerization (Docker), and orchestration (Kubernetes).
- Strong understanding of RESTful APIs, CI/CD pipelines, and Git-based workflows.
Preferred Qualifications
- Experience with distributed training frameworks (e.g., Ray, Ray Tune)
- Knowledge of model explainability, monitoring, and rollback strategies.
- Exposure to hybrid cloud/on-prem infrastructure and HPC environments.
- Prior work on internal platforms or developer tools.
Careers Privacy Statement Keysight is an Equal Opportunity Employer.
Key Responsibilities
- Design and implement MLOps pipelines for training, validation, deployment, and monitoring of machine learning models.
- Develop and maintain infrastructure for data versioning, model registries, and experiment tracking (e.g., MLflow, LakeFS, Airflow).
- Integrate orchestration tools (e.g., Kubeflow, Ray, Airflow) to support automated workflows and distributed training.
- Collaborate with data scientists and software engineers to ensure seamless model handoff and deployment.
- Build APIs and SDKs to abstract infrastructure complexity and enable self-service model development.
- Implement monitoring and alerting systems for model drift, performance degradation, and system health.
- Support on-prem and cloud-based deployments (e.g., Kubernetes, HPC clusters, AWS).
