Data scientist, AX
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Job Location:
Monthly Salary:
Posted on:
16 days ago
Vacancies:
1 Vacancy
Job Summary
Develop and maintain Druid AI knowledge bases - design configure and optimize data ingestion pipelines for both structured and unstructured content.
Integrate Druid AI agents into existing systems ensuring robust API and data
flow connections.
Work on semantic search contextual retrieval and intent-driven reasoning
within Druid AI frameworks.
Collaborate with product and engineering teams to map business use cases into scalable AI workflows.
Continuously monitor evaluate and fine-tune AI performance metrics and
model responses.
Implement best practices for prompt design context chaining and memory
management within Druid.
Document configurations architecture and processes for maintainability and
scalability.
Required Skills & Experience
Hands-on experience with Druid AI - knowledge base creation knowledge
integration and orchestration.
Strong understanding of AI/ML fundamentals LLMs vector databases and retrieval-augmented generation (RAG) concepts.
Proficiency in Python REST APIs and data modeling for AI workflows.
Experience integrating structured (databases APIs) and unstructured (PDFs documents text) data into AI systems.
Familiarity with prompt engineering context management and multi-agent
orchestration.
Understanding of embedding models retrieval pipelines.
Integrate Druid AI agents into existing systems ensuring robust API and data
flow connections.
Work on semantic search contextual retrieval and intent-driven reasoning
within Druid AI frameworks.
Collaborate with product and engineering teams to map business use cases into scalable AI workflows.
Continuously monitor evaluate and fine-tune AI performance metrics and
model responses.
Implement best practices for prompt design context chaining and memory
management within Druid.
Document configurations architecture and processes for maintainability and
scalability.
Required Skills & Experience
Hands-on experience with Druid AI - knowledge base creation knowledge
integration and orchestration.
Strong understanding of AI/ML fundamentals LLMs vector databases and retrieval-augmented generation (RAG) concepts.
Proficiency in Python REST APIs and data modeling for AI workflows.
Experience integrating structured (databases APIs) and unstructured (PDFs documents text) data into AI systems.
Familiarity with prompt engineering context management and multi-agent
orchestration.
Understanding of embedding models retrieval pipelines.
Key Skills
- Laboratory Experience
- Immunoassays
- Machine Learning
- Biochemistry
- Assays
- Research Experience
- Spectroscopy
- Research & Development
- cGMP
- Cell Culture
- Molecular Biology
- Data Analysis Skills
