AI/ML Engineer
Tasks
- Architect RAG pipelines with vector search and hybrid retrieval
- Architect authentication and authorization for AI services
- Author technical design documentation and architecture diagrams
- Build data ETL pipelines for feature engineering and ingestion
- Build production microservices and APIs
- Collaborate with product platform security and operations to ship AI integrations
- Deploy and monitor ML models and AI agent endpoints
- Design AI agent security architectures
- Design production AI agents and multi agent orchestration systems
- Develop evaluation and monitoring frameworks for AI systems
- Integrate third party AI platforms and LLM providers
- Lead architecture reviews and produce implementation roadmaps
Perks/Benefits
- 401k match
- Employee resource groups
- Fertility healthcare
- Flexible WFH
- Flexible remote and in office opportunities
- HSA match
- Medical/Dental/Vision
- Mental health resources
- Paid parental and caregiving leave
- Professional development stipends
- Unlimited PTO
Skills/Tech-stack
AWS SageMaker | Airflow | Apache Spark | Authentication | Authorization | CI/CD | Databricks | Delegated Authorization | Delegated access | ETL | FastAPI | Feature Engineering | Flask | Function Calling | GitHub Actions | Google Vertex | Google Vertex AI | Hybrid retrieval | JavaScript | Jenkins | Kubernetes | LLM chaining | Langchain | Langgraph | Llamaindex | Microservices | Node.js | OAuth | Prompt engineering | Python | RAG | REST API | Terraform | Token Exchange | Token validation | Tool-Calling | TypeScript | Vector Search | Vertex AI
Education
N/A
Roles
AI | AI/ML Engineer | Engineer | ML Engineer
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