AI Engineer - L4
Tasks
- Build data ingestion components
- Build feature engineering components
- Build inference services
- Collaborate on research to production
- Contribute to system design discussions
- Create training evaluation deployment workflows
- Debug issues across LLM layers
- Detect model drift
- Develop supporting APIs
- Evaluate and validate AI models
- Identify hallucinations
- Implement AI-driven features
- Implement LLMOps model deployment
- Implement agentic workflows
- Implement machine learning models
- Implement monitoring and observability
- Maintain engineering documentation
- Manage model versioning
- Manage prompt management
- Orchestrate AI pipelines
- Participate in sprint planning
- Roll out AI features based on performance data
- Track token usage
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | CI/CD | Cloud infrastructure | Data Ingestion | Distributed Systems | Feature Engineering | Infrastructure as Code | LLMOps | Language Models | Language Processing | Large Language Models | MLOps | Machine Learning | Model Monitoring | Natural Language | Natural Language Processing | Observability | Python | Retrieval-Augmented Generation | “as-code”
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
Regions
Countries
States
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