Machine Learning Engineer – Data & Analytics ( 4-6 years Exp) Gurgaon, India- Remote
@Keysight Technologies posted 11 hours ago Shortlist Email JobJob Detail
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Job ID 60243
Job Description
Location: Gurgaon, India
Department: IT
Employment Type: Full-Time (Regular
About the Role
As a Machine Learning Engineer on our Data & Analytics team, you will design, build, and deploy advanced ML models that solve high-impact business problems across multiple domains — from predictive analytics to operational optimization. This role combines data science, MLOps, and cross-functional collaboration to deliver scalable AI-driven insights and automation across the enterprise.
Key Responsibilities
1. Machine Learning Development & Deployment
- Design and implement supervised and unsupervised models for predictive analytics — including churn prediction, demand forecasting, risk scoring, and upsell opportunity identification.
- Translate business problems into end-to-end ML frameworks and production solutions that enhance efficiency, revenue, or customer experience.
- Build and optimize ML pipelines using MLflow, Airflow, Kubeflow, or similar tools.
2. Cross-Functional ML Use Cases
- Partner with business units (Sales, Customer Service, Finance, Supply Chain, and Order Fulfillment) to define and deliver impactful ML use cases.
- Develop domain-specific models and improve them through continuous learning and feedback loops.
3. Model Governance & MLOps
- Implement model monitoring, versioning, and retraining strategies to ensure reliability and performance.
- Collaborate with DevOps and Data Engineering teams to automate CI/CD pipelines and manage cloud-based ML infrastructure (AWS, Azure, or GCP).
4. Data Engineering & Feature Architecture
- Work with data engineers to define feature stores, data quality checks, and model-ready datasets using platforms like Snowflake or Databricks.
- Perform feature selection, transformation, and engineering aligned with domain business logic.
5. Communication & Stakeholder Collaboration
- Present technical insights, model performance, and business impact to executive and cross-functional stakeholders.
- Collaborate with product and program managers to scope, prioritize, and plan ML project delivery.
Qualifications
Required:
- 4–6 years of hands-on experience in Machine Learning, Data Science, or AI Engineering.
- Proficiency in Python and libraries such as scikit-learn, XGBoost, PyTorch, TensorFlow, etc.
- Experience deploying models to production using ML pipelines and orchestration frameworks.
- Strong knowledge of SQL, data structures, and cloud ML platforms (AWS SageMaker, Azure ML, GCP Vertex AI).
Preferred:
- Experience applying ML to Finance, Sales, or Operations use cases.
- Familiarity with MLOps tools like MLflow, SageMaker Pipelines, and Feature Store.
- Exposure to enterprise data platforms such as Snowflake, Oracle Fusion, or Salesforce.
- Background in statistics, forecasting, optimization, or recommendation systems.
Why Join Us?
- Work on enterprise-level ML systems that power decision-making across multiple business functions.
- Collaborate with data scientists, engineers, and business leaders on transformative AI projects.
- Opportunity to shape ML infrastructure and best practices in a global technology organization.
