Manager - Lead AI Engineer
Tasks
- Apply MLOps best practices
- Build and integrate AI APIs
- Collaborate with data scientists and QA teams
- Contribute to version control and performance optimization
- Define AI architecture decisions
- Develop and deploy production AI systems for audit
- Enforce coding standards
- Implement machine learning pipelines
- Implement reusable development patterns
- Integrate data workflows into audit platforms
- Lead technical delivery of AI projects
- Mentor junior engineers
- Share knowledge and build internal capabilities
Perks/Benefits
Skills/Tech-stack
API Authentication | API Design | API authorization | Asynchronous programming | Azure | Azure Machine Learning | Cloud Native | Cloud-native development | Concurrency | Containerization | Databricks | Deep learning | Generative AI | Git | Hugging Face | Hugging Face Transformers | Langchain | Langgraph | Language Processing | MLOps | MLflow | Machine Learning | Multithreading | Native Development | Natural Language | Natural Language Processing | OpenAPI | PySpark | PyTorch | Python | RESTful API | RESTful API design | Scikit-learn | Swagger | Unit Testing
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
AI | AI Engineer | Backend | Backend Engineer | Engineer | Lead | Lead AI | Lead AI Engineer
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