Sr Data Scientist/AI Applications Engineer
Tasks
- Build agents and automation patterns
- Build data pipelines
- Communicate model limitations and assumptions
- Create evaluation benchmarks and test sets
- Define acceptance criteria
- Design human-in-the-loop workflows
- Design workflow solutions
- Develop data and knowledge foundations
- Document data lineage and validation evidence
- Frame AI use cases
- Implement retrieval-augmented generation
- Package reusable prompts and retrieval logic
- Perform error analysis and quality checks
- Support backlog prioritization and release planning
Perks/Benefits
- N/A
Skills/Tech-stack
API Development | Acceptance criteria | Agentic Systems | Benchmarking | Cloud | Data Lineage | Data Pipelines | Data models | Data product | Data product development | Decision Support Systems | Decision support | Documentation | Entity Resolution | Error Analysis | Evaluation methods | Experimental data | Generative AI | Graph Data | Graph data models | Knowledge Management | Machine Learning | Product Development | Python | Reproducible Workflows | Retrieval-Augmented Generation | Scientific metadata | Semantic Querying | Semantic models | Support systems | Test Sets | Testing | Version control | Workflow automation
Education
Roles
AI | AI Engineer | Data Scientist | Engineer | Learning Engineer | Machine Learning Engineer | Scientist
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