AI/ML Engineer
INR 3799K-5000K (estimate) Mid-level Full Time
Tasks
- Build Agentic AI workflows
- Build train evaluate and deploy pipelines
- Collaborate with data engineering for data readiness and quality
- Create batch and real time processing pipelines
- Design machine learning solutions
- Develop AI services and applications
- Develop and deploy machine learning models
- Enable logging metrics monitoring tracing and alerting
- Ensure AI governance security and responsible AI compliance
- Implement MLOps and LLMOps practices
- Implement model deployment monitoring and retraining
- Implement retrieval-augmented generation pipelines
- Integrate LLM orchestration frameworks
- Integrate generative AI into enterprise applications
- Monitor AI system performance accuracy drift and reliability
- Set up experiment tracking and deployment automation
- Support model lifecycle management and version control
- Troubleshoot production issues
Perks/Benefits
Skills/Tech-stack
API Development | AWS | Agentic AI | Alerting | Azure | CI/CD | Deep learning | Docker | Drift monitoring | Embeddings | Experiment tracking | FastAPI | Feature Engineering | Flask | Google Cloud | Human-in-the-loop | Kubernetes | LLMOps | Language Models | Large Language Models | Logging | MLOps | Machine Learning | Metrics | Microservices | Model Deployment | Model Evaluation | Model Monitoring | Model versioning | Observability | Prompt engineering | PyTorch | Python | RAG Pipelines | REST APIs | Retrieval Pipelines | Retrieval-Augmented Generation | SQL | Semantic Retrieval | Semantic Search | Statistical modeling | Supervised Learning | TensorFlow | The Loop | Tool integration | Tracing | Unsupervised Learning | Vector Databases | Vector Search
Education
Roles
AI | AI/ML Engineer | Engineer | Learning Engineer | ML Engineer | Machine Learning Engineer
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