Senior AI Operations Engineer
Tasks
- Architect hybrid AI systems
- Automate model pipelines
- Build GenAI infrastructure
- Create reusable AI infrastructure components
- Deploy RAG microservices
- Ensure HIPAA compliance
- Ensure SOC2 compliance
- Ensure ethical AI practices
- Establish OCI based MLOps best practices
- Identify AI product opportunities from data insights
- Lead AI product initiatives with OCI native services
- Lead generative AI development
- Mentor junior data scientists and engineers
- Serve multimodal LLMs
- Streamline processes with generative AI
Perks/Benefits
- 401k match
- Employee assistance program
- Employee stock purchase plan
- Flexible schedule
- Flexible spending account
- Health insurance
- Life insurance
- Paid parental leave
- Paid sick time
- Paid time off
- Tuition reimbursement
Skills/Tech-stack
AI infrastructure | Azure | CI/CD | Cloud infrastructure | Container Engine for Kubernetes | Data Science | Databricks | Docker | GPU Computing | Generative AI | GitHub Actions | HIPAA | Helm | Hybrid Cloud | Jenkins | Kubernetes | Kubernetes/OKE | LLM Gateway | LLMOps | Language Models | Large Language Models | MLOps | MLflow | Machine Learning | Model versioning | NVIDIA Triton | OCI AI | OCI AI Infrastructure | OCI Container | OCI Container Engine | OCI Container Engine for Kubernetes | OCI Data Science | OCI DevOps | OCI Object Storage | OCI Streaming | Object storage | Oracle Cloud | Oracle Cloud Infrastructure | Private LLM Gateway | RAG | SOC2 | Streamlit | Terraform | VLLM | Vector DB | Vector Database
Education
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