Senior Software Engineer/Applied AI Scientist
INR 2500K-4800K (estimate) Senior-level Full Time
Tasks
- Author prompts and structured outputs
- Build RAG pipelines
- Build synthetic data generation pipelines
- Collaborate with product and risk stakeholders
- Define evaluation metrics and monitoring
- Deploy models with CI CD orchestration
- Design machine learning solutions
- Develop end to end AI lifecycle
- Develop generative AI for compliance automation
- Embed access controls and security into AI design
- Engineer domain knowledge bases
- Implement responsible AI governance
- Implement retrieval strategies and embeddings
- Integrate scoring logic into production systems
- Monitor drift and performance regressions
- Prepare and normalize unstructured data
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | AI Services | ANN indexing | AWS Bedrock | AWS SageMaker | Agent/tool use | Apache Tika | Azure AI | Azure AI Services | B testing | Bias Mitigation | Chunking | Cross-Encoder | Data Generation | Deep learning | Distillation | Docker | Drift Detection | Embeddings | Fairness | Function Calling | Git | Google Vertex | Google Vertex AI | Google Vertex AI RAG Engine | Guardrails | HNSW | Hybrid search | Langchain | Langgraph | Llamaindex | LoRA | MLflow | Machine Learning | NLP | NumPy | OCR | OCR fundamentals | Observability | OpenSearch | PEFT | PGVector | PII Detection | PII Redaction | Pandas | Pdfplumber | Postgres | Prompt engineering | PyMuPDF | PyTorch | Python | RAG | Reranking | Retrieval-Augmented Generation | SQL | Scikit-learn | Series forecasting | Structured Output | Synthetic Data Generation | Synthetic data | TensorFlow | Tesseract | Test set | Test set creation | Time Series | Time Series Forecasting | Tool use | Unix | Vector Search | Vertex AI | Weights and Biases
Education
N/A
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