Principal Data Scientist - AI & Machine Learning (Databricks)
Tasks
- Build Retrieval Augmented Generation systems
- Build data pipelines
- Build intelligent agent applications
- Build semantic search applications
- Collaborate with software engineering teams
- Deploy machine learning models
- Design end-to-end machine learning solutions
- Detect concept drift
- Develop machine learning models
- Evaluate machine learning models
- Implement LLM orchestration workflows
- Mentor junior data scientists
- Monitor model performance
Perks/Benefits
- Career advancement opportunities
- Employee parking
- Employment referral program
- English language development courses
- Flexible work schedule
- Interest-free loans
- Medical insurance
- Social insurance
- Technical development courses
- Training programs
- Travel opportunities
Skills/Tech-stack
AI Search | AWS SageMaker | Amazon Web Services | Apache Spark | Artificial Intelligence | Autogen | Azure | Azure AI | Azure AI Search | Azure Machine Learning | CI/CD | Chroma | Cloud platform | CrewAI | Databricks | Deep learning | Embeddings | Experiment tracking | FastAPI | Feature Engineering | Fine Tuning | Google Cloud | Google Cloud Platform | Google Vertex | Google Vertex AI | Keras | Langchain | Langgraph | Llamaindex | LoRA | MLOps | MLflow | Machine Learning | Milvus | Model Context Protocol | Model Evaluation | Model versioning | Monitoring | Observability | Pinecone | Prompt engineering | PyTorch | Python | Ragas | Retrieval-Augmented Generation | Scikit-learn | Semantic Search | Statistics | Streamlit | TensorFlow | Vector Databases | Vertex AI | Weaviate | Web Services
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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