Machine Learning Engineer

**Designation:** Machine Learning Engineer **Experience:** 6 to 10 years **Qualification:** BE/B.Tech, ME/M.Tech **Location:** Hyderabad, Bangalore and Mumbai **Job Description** As a Machine Learning Engineer, you will own end-to-end ML initiatives from feature engineering and model development to deployment, monitoring, and retraining. You will build production-grade propensity and customer-focused models that drive business decisions, ensuring scalability, reliability, and performance. **Key Responsibilities** - Develop and deploy production-grade ML models for propensity, churn, conversion, and customer analytics. - Own feature engineering, model validation, deployment, monitoring, and retraining. - Implement MLOps practices including model versioning, experiment tracking, CI/CD, and automated retraining. - Monitor model performance, data drift, concept drift, and production issues. - Design scalable and reliable ML architectures and pipelines. - Ensure model explainability, governance, documentation, security, and data privacy. - Collaborate with product, data, and business teams to translate requirements into effective ML solutions. - Leverage LLMs and AI-assisted development tools to improve engineering productivity. **Must-Have Skills** **Technical Skills** - Strong hands-on experience with production ML, Python, and SQL. - Experience with propensity, churn, conversion, or customer-outcome modelling. - Strong knowledge of feature engineering, feature stores, data leakage prevention, and train/serve consistency. - Experience with ML validation, backtesting, A/B testing, and model performance measurement. - Hands-on experience with MLOps, MLflow/model registry, CI/CD, model monitoring, and automated retraining. - Understanding of data drift, concept drift, model governance, explainability, and model security. - Ability to design scalable, reliable, and maintainable ML solutions. **AI LLM Skills (Mandatory)** - Strong hands-on experience using LLMs and AI-assisted development tools in day-to-day engineering. - Experience with prompt engineering, coding agents, AI-assisted development, and LLM workflow integration. - Practical experience with tools such as Claude, Cursor, GitHub Copilot, or equivalent. - Ability to evaluate LLM output, identify limitations, and use AI tools effectively in production engineering. **Professional Skills** - Strong problem-solving, analytical, and systems-thinking skills. - Strong ownership and ability to work independently in a fast-paced environment. - Good communication and stakeholder management skills. - Ability to explain ML concepts and technical decisions to non-technical stakeholders. Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.