Data Scientist NLP (AI) Engineer
Tasks
- Build LLM evaluation frameworks
- Build reusable Python components and APIs
- Communicate technical findings to stakeholders
- Create data pipelines for structured and unstructured data
- Design LLM-powered applications
- Develop AI solutions on Google Cloud Platform
- Develop experimentation and feedback loops
- Develop prompt strategies
- Implement agentic AI workflows
- Implement model monitoring and guardrails
- Perform exploratory analysis and feature engineering
- Translate emerging generative AI methods into production value
Perks/Benefits
- N/A
Skills/Tech-stack
APIs | Access Management | Adversarial Testing | Agent systems | Agentic AI | BigQuery | BigQuery ML | CI/CD | Cloud Computing | Cloud Functions | Cloud Run | Cloud Storage | Cloud platform | Containers | Dataflow | Experiment tracking | Fine Tuning | Generative AI | Git | Google Cloud | Google Cloud Platform | Human In The Loop Approvals | Human-in-the-loop | Identity and Access Management | Identity and access | LLMOps | Language Models | Language Processing | Large Language Models | MLOps | Machine Learning | Model Evaluation | Model Monitoring | Multi-Agent | Multi-Agent Systems | Natural Language | Natural Language Processing | Prompt engineering | Pub/Sub | Python | Red Teaming | SQL | Safety in AI | The Loop | Tool-Calling | Vertex AI | Workflow Orchestration
Education
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