GCP AI Engineer - Cambridge, MA
Tasks
- Apply IAM VPC encryption and secure access
- Build RAG and conversational AI systems
- Build secure data pipelines with validation checks
- Collaborate with clinical, product, and engineering teams
- Deploy and monitor ML models in production
- Deploy workflow automation models
- Design AI solutions on Google Cloud
- Detect model drift and improve performance
- Develop Generative AI and Agentic systems
- Develop clinical decision support models
- Ensure HIPAA compliance
- Implement end-to-end ML pipelines
- Integrate EHR data using FHIR and HL7
- Prototype and validate new AI workflows
- Support EMR interoperability
- Troubleshoot distributed AI production issues
- Use Cloud Operations for monitoring and alerting
Perks/Benefits
- 401k match
- Disability insurance
- Employee assistance program
- Employee discount program
- Employee resource groups
- Health savings account
- Hybrid work schedule
- Learning and development opportunities
- Life insurance
- Medical/Dental/Vision insurance
- Paid time off
- Volunteer and wellness days
Skills/Tech-stack
AI Ops | BigQuery | Cloud Build | Cloud Operations | Cloud platform | Dataflow | Docker | EHR | EMR | Encryption | FHIR | Gemini API | Google Cloud | Google Cloud Platform | HIPAA | HL7 | IAM | Kubeflow | Kubernetes | Langchain | Langgraph | Learning operations | Looker | ML Pipeline | MLOps | Machine Learning | Machine Learning Operations | Model Monitoring | Python | RAG | Terraform | VPC | Vertex AI
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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