Machine Learning Engineer

Designation: Machine Learning EngineerExperience: 6 to 10 yearsQualification: BE/B.Tech, ME/M.TechLocation: Hyderabad, Bangalore and MumbaiJob DescriptionAs 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 SkillsTechnical 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.