ML Engineer

ML Engineer | 3+ years | Remote | Work Timing: Standard IST Job Description: We are looking for a skilled Machine Learning Engineer with hands-on experience deploying models on Google Cloud Platform (GCP) using Vertex AI. This role involves enabling real-time and batch model inferencing based on specific business requirements, with a strong focus on production-grade ML deployments. Key Responsibilities: Deploy machine learning models on GCP using Vertex AI. Design and implement real-time and batch inference pipelines. Monitor model performance, detect drift, and manage lifecycle. Ensure adherence to model governance best practices and support ML-Ops workflows. Collaborate with cross-functional teams to support Credit Risk, Marketing, and Customer Service use cases, especially within the retail banking domain. Develop scalable and maintainable code in Python and SQL. Work with diverse datasets, perform feature engineering, and build, train, and fine-tune advanced predictive models. Contribute to model deployment in the lending space. Required Skills & Experience: Strong expertise in Python and SQL. Proficient with ML libraries and frameworks such as scikit-learn, pandas, NumPy, spaCy, CatBoost, etc. In-depth knowledge of GCP Vertex AI and ML pipeline orchestration. Experience with ML-Ops and model governance. Exposure to use cases in retail banking—Credit Risk, Marketing, and Customer Service. Experience working with structured and unstructured data. Nice to Have: Prior experience deploying models in the lending domain. Understanding of regulatory considerations in financial services. Job Type: Contractual / Temporary Contract length: 6 months Pay: ₹70,000.00 - ₹80,000.00 per month Benefits: Work from home Schedule: Monday to Friday Morning shift UK shift US shift Application Question(s): Are you ready to move Onsite | Bangalore/Pune? Education: Bachelor's (Preferred) Experience: ML Engineer: 3 years (Required)