Sr. AI Engineer
Tasks
- Apply MLOps best practices
- Build and optimize end-to-end data pipelines
- Deploy and manage scalable AI solutions on GCP
- Design and deploy AI ML and generative AI models
- Develop and fine-tune generative ai models
- Ensure responsible AI fairness transparency and explainability
- Implement LLM retrieval augmented generation and agentic frameworks
- Implement LLM security output moderation access control and auditability
- Integrate LLMs with enterprise systems using REST APIs and SDKs
- Integrate data warehousing solutions and manage data pipelines
Perks/Benefits
- 401-k match
- Dental insurance
- Expense Reimbursement for Home Office
- Life insurance
- Medical insurance
- Paid time off
- Vision insurance
- Wellness programs
Skills/Tech-stack
Access Control | Agentic Frameworks | Auditability | CI/CD | Cloud Native | Cloud-native AI | Data Pipelines | Data Warehousing | Docker | Drift analysis | Explainability | Fairness | GCP | Generative AI | GitLab | Language Models | Large Language Models | MLOps | MLflow | Machine Learning | Model versioning | Output moderation | Prompt engineering | PySpark | Python | Quantization | REST APIs | Retrieval-Augmented Generation | SDKs | SQL | Security | Snowflake | T-SQL | Transparency | Version control
Education
Roles
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