GCP AI Engineer - Cambridge, MA
Tasks
- Apply IAM VPC encryption security best practices
- Build agentic and generative AI systems
- Build and optimize end-to-end ML pipelines
- Build, test, and deploy AI/ML models
- Construct secure compliant healthcare data pipelines
- Define problem with stakeholders
- Design and deploy RAG systems
- Detect drift and update models
- Embed AI agents into clinical workflows
- Ensure HIPAA compliance
- Implement data validation and quality checks
- Monitor reliability and troubleshoot production issues
- Own AI features end-to-end
- Support EHR FHIR HL7 integration
- Train validate deploy and monitor models
Perks/Benefits
- 401k match
- Disability insurance
- Employee assistance program
- Employee discount program
- Employee resource groups
- FSA
- HSA
- Hybrid work schedule
- Learning and development
- Life insurance
- Medical, Vision, Dental plans
- Paid time off
Skills/Tech-stack
BigQuery | Cloud Build | Cloud Operations | Cloud platform | Conversational AI | Data Interoperability | Dataflow | Docker | EHR | EMR | Encryption | Epic | FHIR | Gemini API | Google Cloud | Google Cloud Platform | HIPAA | HL7 | Healthcare Data | Healthcare data interoperability | IAM | Kubeflow | Kubernetes | Langchain | Langgraph | Looker | ML Ops | MLOps | Machine Learning | Model Monitoring | Python | Retrieval-Augmented Generation | Stackdriver | Terraform | VPC | Vertex AI
Education
Roles
AI | AI Engineer | Engineer | GCP AI Engineer | Learning Engineer | Machine Learning Engineer
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