Senior AI / MLOps Engineer – Clinical AI
Tasks
- Apply containerization and Infrastructure as Code
- Automate ML lifecycle tasks
- Build, deploy, and maintain CI/CD pipelines
- Collaborate with cross-functional teams
- Design and implement cloud infrastructure
- Develop scalable inference pipelines and APIs
- Implement monitoring and performance dashboards
- Integrate NLP and generative AI solutions
- Optimize models for latency throughput and cost
- Own the full machine learning lifecycle
- Participate in system design and architecture
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Alerting | Azure | CI/CD | Classification | Docker | Embeddings | Generative AI | Infrastructure as Code | Java | Kubeflow | Kubernetes | LLMs | MLflow | Model Optimization | Monitoring | NLP | Performance dashboards | Python | SageMaker | Sequence Modeling | Tokenization | “as-code”
Education
Roles
AI | AI Engineer | Engineer | MLOps Engineer
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