IN_Senior Associate_GEN AI_Data and Analytics_Advisory_Noida
Tasks
- Build model retraining workflows
- Containerize services with Docker
- Create data visualizations
- Deploy models on Kubernetes
- Design machine learning pipelines
- Design model inference APIs
- Develop statistical modeling for insights
- Fine-tune large language models
- Implement MLOps practices
- Implement data manipulation and analysis
- Manage machine learning experiments
- Manage machine learning models
- Optimize distributed training for large language models
- Optimize training and resource usage
- Orchestrate LLM workflows
- Reduce latency and improve accuracy
- Serve large language models
Perks/Benefits
- N/A
Skills/Tech-stack
AWS Bedrock | Amazon Aurora | Amazon DynamoDB | Amazon RDS | Amazon SageMaker | Azure AI | Azure Solutions Architecture | Azure solutions | Cloud Spanner | Cosmos DB | DeepSpeed | Distributed Training | Docker | Fine Tuning | Flowise | Fluentd | GPU Architecture | Generative AI | Google BigQuery | Google Cloud | Google Cloud Spanner | Grafana | Hugging Face | JavaScript | Keras | Kibana | Kubernetes | LLM orchestration | LLM serving | LLMOps | Langchain | Langgraph | Language Model | Large Language Model | Llamaindex | MLflow | Machine Learning | Model Fine-tuning | MongoDB | MySQL | PostgreSQL | Prometheus | PyTorch | Python | SQL | Solutions Architecture | TensorFlow | VLLM | Vertex AI
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