AI / Analytics Engineer
Mid-level Full Time
Tasks
- Build and maintain data ingestion transformation semantic layers and feature engineering pipelines
- Define success metrics validate assumptions and improve solutions
- Design and implement agentic AI workflows
- Design develop and deploy analytics solutions
- Develop and operationalize GenAI solutions
- Develop and operationalize machine learning models
- Evaluate emerging AI and analytics technologies
- Implement MLOps and LLMOps practices
- Optimize models and pipelines for performance reliability cost and scalability
- Promote responsible ethical AI and regulatory compliance
- Prototype experiment and iterate on AI solutions
- Support production deployment and monitoring of models and data quality
- Translate business needs into technical designs and data requirements
Perks/Benefits
- N/A
Skills/Tech-stack
Agentic AI | Bias Mitigation | Data Ingestion | Data Modeling | Data Transformation | Feature Engineering | GenAI | LLMOps | Language Models | Language Processing | Large Language Models | MLOps | Machine Learning | Model Evaluation | Monitoring | Natural Language | Natural Language Processing | Prompt engineering | Python | RAG | Retrieval-Augmented Generation | SQL | Semantic layer | Testing | Version control | Workflow Orchestration
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | Analytics | Analytics Engineer | Engineer | Learning Engineer | Machine Learning Engineer
Regions
Countries
Brazil | Guatemala | Mexico | Philippines
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