Keysight is Hiring for Machine Learning Engineer

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Job Overview

Keysight is seeking a Machine Learning Engineer to develop, deploy, and optimize advanced ML models across multiple business domains including Sales, Service, Finance, Supply Chain, and Order Fulfillment. This role demands a strong foundation in ML/AI, data engineering, and MLOps, combined with the ability to translate business problems into scalable solutions. The ideal candidate will collaborate with cross-functional teams to deliver impactful production-ready ML applications.

Job Details

Company: Keysight Technologies
Job Position: Machine Learning Engineer – Data and Analytics
Location: Bangalore, India
Qualification: Bachelor’s/Master’s in Computer Science, Data Science, AI/ML, or related field
Experience: 4–6 years in ML/AI engineering or Data Science
Salary: ₹18–26 LPA (based on industry standards and experience)

Key Responsibilities

  1. Design supervised and unsupervised ML models for predictive analytics.
  2. Build models for churn prediction, demand forecasting, and fraud detection.
  3. Deploy ML solutions into production using scalable pipelines.
  4. Collaborate with data scientists, engineers, and domain experts.
  5. Implement MLOps practices including CI/CD workflows and monitoring.
  6. Optimize and maintain pipelines using MLflow, Airflow, or Kubeflow.
  7. Develop lead scoring and next-best action models for Sales teams.
  8. Create case deflection and sentiment analysis solutions for Customer Service.
  9. Implement risk scoring and forecasting models for Finance teams.
  10. Develop delivery risk and ETA prediction models for Supply Chain.
  11. Define feature stores and data engineering workflows with Snowflake/Databricks.
  12. Conduct feature engineering, selection, and transformation.
  13. Continuously retrain and improve models based on live performance.
  14. Translate ML outputs into actionable insights for stakeholders.
  15. Ensure all ML solutions align with compliance and governance standards.

Required Skills and Knowledge

  1. Strong expertise in Python for ML development.
  2. Hands-on with ML libraries such as TensorFlow, PyTorch, scikit-learn, and XGBoost.
  3. Experience deploying ML models into production environments.
  4. Solid foundation in SQL and data structures.
  5. Familiarity with cloud-based ML platforms like AWS SageMaker, Azure ML, or GCP Vertex AI.
  6. Understanding of forecasting, optimization, and recommendation algorithms.
  7. Experience with enterprise data platforms such as Snowflake or Oracle Fusion.
  8. Knowledge of Salesforce and other enterprise applications is a plus.
  9. Strong grounding in statistics and applied mathematics.
  10. Familiarity with MLOps tools such as MLflow or Kubeflow.
  11. Experience in CI/CD workflows for ML deployment.
  12. Problem-solving ability with strong debugging skills.
  13. Effective communication for technical and business audiences.
  14. Ability to work with multiple business units simultaneously.
  15. Strong collaboration skills for cross-functional teamwork.
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About Keysight Technologies

Keysight Technologies is a global leader in electronic design, test, and measurement solutions with operations in more than 100 countries. With over 15,000 employees, Keysight drives innovation across communications, 5G, automotive, aerospace, defense, semiconductors, and emerging quantum technologies. The company is known for its pioneering culture, cutting-edge R&D, and strong focus on delivering trusted insights that enable industry leaders to build world-class solutions.

Why Join Keysight Technologies

  1. Work with a global leader in electronic design and testing.
  2. Exposure to projects across multiple industries such as 5G, automotive, and aerospace.
  3. Opportunity to work on cutting-edge ML/AI solutions.
  4. Collaborative culture encouraging innovation and creativity.
  5. Strong focus on diversity, inclusion, and belonging.
  6. Career growth opportunities in emerging technologies.
  7. Hands-on exposure to enterprise-scale ML deployment.
  8. Learning opportunities with advanced ML tools and platforms.
  9. Work alongside global experts in data science and AI.
  10. Access to advanced cloud infrastructure for ML experimentation.
  11. Competitive compensation aligned with industry standards.
  12. Work-life balance with flexible policies.
  13. Contribution to impactful, real-world business challenges.
  14. Recognition for innovation and creative solutions.
  15. Stability of working with a globally trusted brand.

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