Lead AI/ML Engineer – Predictive Maintenance
INR 2535K-4512K (estimate) Senior-level Full Time
Tasks
- Analyze operational fleet data
- Apply MLOps for model lifecycle
- Apply explainable AI privacy preserving methods and federated learning
- Build and productionize machine learning models
- Conduct AI testing verification and validation
- Coordinate cross-functional teams
- Create innovation and support patent filings
- Design diagnostic prognostic architectures
- Develop explainable dashboards and visualizations
- Develop remaining useful life algorithms
- Drive test driven development
- Enforce data governance, security, and compliance
- Implement anomaly detection and fault isolation
- Implement edge cloud analytics architecture
- Lead AI/ML projects
- Manage Agile/ Scrum delivery
- Run proofs of concept and pilot evaluations
- Translate requirements into tasks
Perks/Benefits
Skills/Tech-stack
Adversarial Testing | Anomaly Detection | Cloud Computing | Data Lakes | Docker | Edge Computing | Explainable AI | Fault isolation | Federated Learning | Generative AI | Kalman Filter | Knowledge graphs | Kubernetes | LLMs | MLOps | MLOps model registry | Machine Learning | Model Registry | Model calibration | NLP | NoSQL | NumPy | Pandas | Power BI | Predictive Maintenance | Privacy-preserving | Privacy-preserving machine learning | Probabilistic Modeling | PyTorch | Python | RAG | Reliability modeling | Remaining useful life | SQL | Scikit-learn | Semantic Search | Tableau | TensorFlow | Test-Driven | Test-Driven Development | Time Series | Time-series databases | Uncertainty Estimation | Vector Databases
Education
Bachelor of Engineering | Bachelor of Science | Bachelor of Technology
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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