AI Engineer Global IT Infrastructure
Tasks
- Apply responsible AI checks for bias fairness and privacy
- Build and maintain ML pipelines for ingestion preprocessing and training
- Build retrieval-augmented generation pipelines
- Build tool augmented agents
- Build, train, and evaluate machine learning models
- Collaborate with data and platform engineers
- Conduct exploratory data analysis and feature engineering
- Deploy and serve machine learning models
- Develop and maintain generative AI applications
- Develop evaluate and support LLM proof of concepts
- Implement infrastructure as code for AI workloads
- Implement monitoring and logging for auditability
- Implement prompt engineering patterns
- Monitor models for drift and performance degradation
- Participate in Agile ceremonies and sprint planning
- Produce model cards data lineage and risk documentation
- Support model validation testing and benchmarking
- Write testable well-documented code
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Anthropic API | Azure | CI/CD | ChromaDB | Cloud platform | DVC | Docker | Git | Google Cloud | Google Cloud Platform | Huggingface | Infrastructure as Code | LLM APIs | Langchain | Llamaindex | MLOps | MLflow | Machine Learning | Monitoring and Logging | NumPy | OpenAI API | PGVector | Pandas | Pinecone | Prompt engineering | PyTorch | Python | Responsible AI | Retrieval-Augmented Generation | Scikit-learn | TensorFlow | Vector Databases | Weaviate | Weights and Biases | “as-code”
Education
Bachelor of Arts | Bachelor of Engineering | Bachelor of Mathematics | Bachelor of Science
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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