Principal Data Scientist
Tasks
- Automate model deployment
- Build CI/CD pipelines for ML
- Build and deploy Agentic applications
- Build and deploy large language model solutions
- Build and deploy machine learning models
- Collaborate with product data engineering stakeholders
- Design production ready AI ML systems
- Evaluate and integrate LLM and agentic frameworks
- Implement MLOps practices
- Implement continuous training
- Implement model tracking
- Influence AI technology roadmap decisions
- Lead AI/ML system architecture
- Mentor ML engineers and conduct peer reviews
- Optimize data and model pipelines
- Write production code
Perks/Benefits
- Annual leaves
- Discount Portal
- Employee assistance program
- Flexible spending account
- Life and accident insurance
- Lunch pass card
- Multi-sport card
- Pension plan
- Private medical insurance
- Reimbursement for Corrective Glasses
- Reimbursement for remote work expenses
Skills/Tech-stack
AWS | Agentic Workflows | CI/CD | Classification | Cloud platform | Clustering | Data Structures | Deep learning | Docker | Google Cloud | Google Cloud Platform | Kubernetes | Language Models | Large Language Models | MLOps | Machine Learning | Microsoft Azure | Model Tracking | Python | Regression | Serverless | System design
Education
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