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.

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 :

- 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.