AI Engineer
Tasks
- Build data pipelines and orchestration systems
- Build model serving and monitoring pipelines
- Collaborate to identify new AI use cases
- Deploy custom AI services with foundational models
- Deploy fine tuning methodologies
- Design agent to agent workflows
- Design reliable scalable AI service architecture
- Develop APIs for low latency high availability services
- Implement Model Context Protocol (MCP)
- Implement Retrieval-Augmented Generation (RAG)
- Implement observability and evaluation systems
- Integrate LLM prototypes into production
- Measure output quality and run A B tests
- Refactor, deploy, and maintain AI services
Perks/Benefits
- Additional paid leave
- Fitness and wellness memberships
- Language apps
- Personal development budget
- Premium bank account subscription
- Public transportation
- Relocation package with visa support
- Work from home budget
Skills/Tech-stack
A I | A I Agent | A I Agent Orchestration | A/B | A/B Testing | API Design | AWS | AWS Bedrock | Agent Orchestration | Amazon SageMaker | B testing | Data Pipelines | Docker | Feature Stores | Google Vertex | Google Vertex AI | Kotlin | Kubernetes | Language Models | Large Language Models | Logging | MLOps | Machine Learning | Metrics | Microservices | Observability | Prompt engineering | Python | Retrieval-Augmented Generation | Tracing | Vector Databases | Vertex AI
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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