Data Scientist 2
Tasks
- Build RAG and LLM agentic solutions
- Build reusable ML infrastructure
- Collaborate with ML Engineering and Data Engineering teams to deliver scalable systems
- Convert business workflows into ML problem statements
- Create offline and online evaluation frameworks
- Define guardrails evaluation and explainability
- Deploy production-grade AI systems
- Develop ML models for ETA risk anomaly and fraud
Perks/Benefits
- N/A
Skills/Tech-stack
Airflow | Bias detection | Data Drift | Data Quality | Databricks | Deep learning | Distributed Systems | Embeddings | Experimentation | Feature Engineering | Kafka | Language Models | Large Language Models | MLOps | Machine Learning | Model Evaluation | Model Monitoring | Probabilistic Modeling | Python | RAG | REST APIs | SQL | Snowflake | Spark | Transformer Models | Tree-based Models | Vector Databases
Education
N/A
Roles
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