AI Developer
Tasks
- Apply AIOps for incident detection and optimization
- Architect generative AI platforms
- Build Retrieval Augmented Generation systems
- Collaborate with data scientists, software engineers, and product teams
- Deploy models with Docker and Kubernetes
- Design AI models and algorithms
- Develop LLM applications
- Document workflows and models
- Implement MLOps pipelines
- Implement vector databases and inference pipelines
- Monitor model performance and retrain
- Perform data preprocessing and analysis
- Prototype proof-of-concept solutions
- Train, validate, and fine-tune ML models
Perks/Benefits
- N/A
Skills/Tech-stack
AIOps | AWS | Agile | Azure | Cloud Computing | Docker | Embeddings | GCP | GitHub Copilot | Infrastructure as Code | Knowledge graphs | Kubernetes | Langchain | Language Models | Large Language Models | MLOps | Machine Learning | OpenCV | PyTorch | Python | RAG | Retrieval-Augmented Generation | Scikit-learn | Semantic Search | Streamlit | TensorFlow | Vector Databases | Vectorization | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Developer | Developer | Engineer | Learning Engineer | Machine Learning Engineer
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