Responsibilities
- AI/ML Model Development
- Design, build, fine tune and train machine learning and deep learning models using Python.
- Perform data preprocessing, feature engineering, and model optimization.
- Evaluate models using domain appropriate metrics and improve performance iteratively.
- Deploy custom models to production environments (cloud/on-premises) using MLOps best practices.
- Full-Stack Development
- Develop high throughput, event-driven microservices (RESTful APIs, GraphQL) for application backends and MCP servers to serve AI models.
- Build responsive and user-friendly front-end interfaces for AI-powered applications.
- Integrate AI models into web and mobile applications.
- Ensure scalability, security, and performance of deployed solutions.
- Collaboration & Documentation
- Work closely with data scientists, developers, frontend developers, and product managers.
- Document model architectures, APIs, and deployment processes.
- Participate in code reviews and maintain high coding standards.
Requirements
- Expertise in machine learning model creation
- Expertise in full-stack application development
- Build high performance Python-based AI/ML solutions capable of processing extremely large data sets
- Integrate AI/ML solutions into scalable web applications, including LLMs
- Strong problem-solving skills
- Deep understanding of AI frameworks
- Ability to work across the entire technology stack
Work Arrangement
Hybrid
