Sr. Applied AI Engineer
Tasks
- Analyze data with statistical methods and machine learning
- Build data mining architectures models and protocols
- Build microservices or APIs for business logic
- Build reusable software components or libraries
- Create presentations to report methodology and analysis results
- Deploy predictive models and support customer issue triage
- Develop and code algorithms and automated processes to cleanse and integrate datasets
- Develop predictive models for customer behavior and future predictions
- Develop security features and adopt DevSecOps culture
- Identify and mitigate production incidents using monitoring tools
- Identify data analysis questions and experiments
- Produce statistical reporting and trend analysis
- Research apply and educate on data science techniques
- Support streaming and at rest processing for customer centric models
Perks/Benefits
- N/A
Skills/Tech-stack
API Development | Agile Scrum | Apache Flink | Apache Spark | Data Mining | Data Normalization | Data Parsing | Data Processing | Data cleaning | DevSecOps | Distributed data | Distributed data processing | Docker | Embeddings | GitHub | Jira | Language Models | Language Processing | Large Language Models | MLOps | Machine Learning | Microservices | Natural Language | Natural Language Processing | Optimization | Predictive Modeling | Prompt Guardrails | Prompt engineering | Python | Retrieval-Augmented Generation | Secure Data | Secure data processing | Semantic Search | Statistical Analysis | Streaming Data | Unit Testing | Vector Databases
Education
N/A
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