Sr. Applied AI Engineer
Tasks
- Analyze large datasets with statistical methods
- Build data mining architectures models and protocols
- Build reusable software components
- Build scalable AI ML pipelines and deploy models
- Create predictive models for customer behavior
- Develop data cleansing integration evaluation pipelines
- Develop microservices and APIs
- Develop optimization tools and customer centric models
- Evaluate fine tune and optimize LLM solutions
- Extract insights from historical patterns
- Identify data analysis questions
- Implement RAG and semantic search
- Implement security features with DevSecOps
- Integrate LLMs into production applications
- Monitor and govern generative AI systems
- Prepare analysis reports and presentations
- Research and apply data science techniques
- Support production deployments and incident triage
Perks/Benefits
- N/A
Skills/Tech-stack
Agile Scrum | Apache Flink | Apache Spark | Containerization | Data Mining | Docker | Embeddings | GitHub | Guardrails | Jira | LLM APIs | Language Processing | MLOps | Machine Learning | Microservices | Model Monitoring | Natural Language | Natural Language Processing | Predictive Modeling | Prompt Optimization | Prompt engineering | Python | REST APIs | Retrieval-Augmented Generation | Semantic Search | Statistical Analysis | Unit Testing | Vector Databases
Education
N/A
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