Key responsibilities
- Translate business problems into measurable machine-learning objectives and evaluation criteria.
- Perform exploratory analysis, data preprocessing, feature engineering and feature selection.
- Develop and compare supervised, unsupervised and deep-learning models as appropriate.
- Execute hyperparameter tuning, cross-validation, error analysis and model explainability.
- Build reusable training, validation and inference pipelines in Python.
- Deploy batch and real-time inference services using APIs or managed cloud endpoints.
- Monitor model quality, drift, latency, reliability and cost after deployment.
- Collaborate with data engineers to define reliable data inputs and feature pipelines.
- Apply engineering standards for testing, versioning, documentation and reproducibility.




- Contribute to architecture decisions for scalable and secure AI/ML systems.

Required qualifications and experience
- 5+ years of relevant experience in machine learning, applied data science or AI engineering.
- Solid Python, data manipulation and machine-learning implementation skills.
- Demonstrable experience taking models from experimentation to production.
- Experience with at least one cloud platform: AWS, Microsoft Azure or Google Cloud Platform.
- Strong understanding of model evaluation, statistical reasoning and business-aligned metrics.
- Ability to communicate trade-offs among model quality, latency, scalability and cost.

📌 AIML Engineer (Bengaluru)
🏢 IndiHire Consultants
📍 Bengaluru