Sr. AI Engineer-Promo Optimisation
Tasks
- Build and deploy REST APIs microservices and model serving endpoints
- Build production grade AI ML applications services and platforms
- Convert prototypes notebooks and optimization algorithms into production ready systems
- Design scalable data and ML pipelines for batch streaming and near real time
- Design scalable inference systems for promotion decisioning segmentation and offer ranking
- Evaluate and integrate Generative AI and LLM components with RAG workflows
- Explore agentic AI workflows with planning tool use and human in the loop
- Implement MLOps capabilities for model registry experiment tracking and automated retraining
- Implement end to end model training evaluation deployment inference monitoring and lifecycle management
- Implement observability and reliability with logging metrics traces and alerting
- Optimize AI ML services for latency throughput cost scalability and reliability
- Store retrieve transform and manage structured and unstructured data for AI ML
- Support production deployment and release management with CI CD and containers
- Troubleshoot production issues across pipelines model services and integrations
Perks/Benefits
- N/A
Skills/Tech-stack
Alerting | Artificial Intelligence | CI/CD | Data Drift | Data Drift Detection | Docker | Drift Detection | Embeddings | Event Driven | Event-driven architecture | Experiment tracking | Feature Engineering | Feature Store | Generative AI | Guardrails | Hadoop | Hive | Kafka | LLM | Logging | MLOps | Machine Learning | Metrics | Microservices | Model Deployment | Model Drift | Model Drift Detection | Model Evaluation | Model Monitoring | Model Registry | NoSQL | Observability | Prompt engineering | Python | REST APIs | Retrieval-Augmented Generation | SQL | Spark | Tracing | Vector Databases | Workflow Orchestration
Education
Bachelor of Engineering | Bachelor of Science | Bachelor of Technology | Master of Science
Roles
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