Senior Applied AI Engineer
Tasks
- Address scalability and performance with large scale computing
- Build AI driven products with foundation models
- Debug production code
- Design scalable AI systems with C#
- Design scalable AI systems with Python
- Develop LLM prompts and agent workflows
- Develop multi-agent architectures
- Ensure responsible AI practices for fairness bias and privacy
- Evaluate model behavior for bias hallucination and relevance
- Fine-tune foundation models
- Implement RAG systems
- Implement state of the art using prompt engineering
- Maintain documentation of experiments results and methodologies
- Measure impact with A B testing and telemetry
- Monitor model behavior and alerts
- Prepare data for machine learning feature engineering
- Prototype AI solutions and support production deployment
- Support MLOps and AIOps
- Train and evaluate machine learning models
- Translate research into production-ready solutions
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | AIOps | Agent systems | B testing | Bias Mitigation | C# | CI/CD | Data Preparation | Deep learning | Feature Engineering | Fine Tuning | Foundation Models | Generative AI | Graph reasoning | Hallucination Evaluation | LLM | Langchain | Language Processing | MLOps | Machine Learning | Model Monitoring | Multi-Agent | Multi-Agent Systems | Multimodal Models | Natural Language | Natural Language Processing | Optimization | Prompt engineering | PromptFlow | Python | RAG | Retraining Pipelines | Statistical Analysis | Telemetry
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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