Job Description
Job Description:
1. Design, develop, test, and deploy machine learning, Generative AI, and AI-driven applications based on business requirements.
2. Develop and integrate LLM-based solutions using prompt engineering, RAG, embeddings, vector databases, and AI APIs.
3. Build reusable Python-based components, APIs, and services to support AI and machine learning applications.
4. Perform data preparation, feature engineering, model training, evaluation, optimization, and performance monitoring.
5. Work with cloud-based AI and data services, preferably Microsoft Azure, AWS, or Google Cloud.
6. Develop and integrate REST APIs, databases, enterprise applications, and external data sources into AI solutions.
7. Implement responsible AI practices including security, data privacy, model governance, explainability, and monitoring.
8. Collaborate with data engineers, software developers, architects, business analysts, and stakeholders to deliver end-to-end AI solutions.
9. Troubleshoot model, application, and integration issues and continuously improve solution accuracy, scalability, reliability, and performance.
10. Stay current with emerging AI, Generative AI, Agentic AI, machine learning frameworks, and industry best practices and contribute to AI innovation initiatives.
More Info
Key Skills
feature engineering
responsible AI practices
cloud-based AI and data services
RAG embeddings
explainability
AI-driven applications
LLM-based solutions
AI APIs
AI innovation initiatives
model governance
vector databases
model training
Generative AI
prompt engineering
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