Job Description
About the Role
We are seeking a talented and motivated AI/ML Engineer to support the development of advanced AI and machine learning solutions. In this role, you will design, develop, and deploy AI/ML models that enhance our products and technologies.
Experience in AI/ML development, a strong foundation in data-driven modeling, and a passion for applying advanced analytics to real-world problems. You will collaborate closely with engineers, data scientists, and product managers to develop innovative solutions that provide measurable impact.
Why Keysight
- Contribute to cutting-edge AI/ML solutions in a global technology leader.
- Collaborate with teams across multiple disciplines and geographies.
- Work in a high-impact, innovative environment solving challenging problems.
- Competitive compensation, benefits, and career growth opportunities.
Responsibilities
- Design, develop, and deploy AI/ML models to support R&D; and product initiatives.
- Collaborate with cross-functional teams to translate business and technical requirements into actionable AI solutions.
- Analyze large datasets to extract insights and optimize model performance.
- Implement scalable and maintainable AI/ML pipelines and frameworks.
- Conduct experiments, validate models, and iterate based on results.
- Stay up-to-date with the latest AI/ML research and techniques relevant to your work.
- Communicate technical findings clearly to both technical and non-technical stakeholders.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Data Science, or a related field.
- Relevant professional experience in AI/ML development.
- Strong programming skills in Python, C++, or similar languages.
- Hands-on experience with machine learning frameworks (TensorFlow, PyTorch, Scikit-learn, etc.).
- Experience in data preprocessing, feature engineering, model training, and evaluation.
- Excellent problem-solving, analytical, and communication skills.
Nice to have:
- Experience applying AI/ML to complex engineering or technical problems.
- Knowledge of cloud-based ML platforms or distributed training environments.
- Experience with AI/ML model deployment and productionization.
