Role & responsibilities
1. Develop and optimize our large language model-based SaaS application.
2. Employ Fast API to build robust APIs and aid in backend service management.
3. Implement and optimize specialized databases for semantic working.
4. Focus on model thought logic to improve the application's AI capabilities.
5. Innovate in unstructured document processing, enabling the application to handle diverse data types.
6. Utilize Docker for service containerization and efficient deployments.
7. Collaborate effectively with a Coding Copilot, enhancing productivity and code quality.
8. Research and Development: Staying up-to-date with the latest advancements in natural language processing and AI research to incorporate cutting-edge techniques into your projects.
9. Troubleshooting and Bug Fixing: Identifying and resolving issues related to the GPT model's performance, data handling, or integration with other components.
10. Security and Privacy Considerations: Taking into account security and privacy concerns related to AI models and data handling, adhering to best practices and compliance standards.
11. Deployment and Scalability: Deploying GPT-powered applications in production environments and considering scalability to handle varying workloads.
Preferred candidate profile
1. Strong Programming Skills: Proficiency in Python is essential, as the role involves working extensively with Python libraries and frameworks for natural language processing and deep learning (e.g., TensorFlow, PyTorch, Hugging Face Transformers).
2. Deep Learning and NLP Knowledge: Solid understanding of deep learning concepts and natural language processing techniques, including neural networks, attention mechanisms, sequence-to-sequence models, and transfer learning.
3. Data Handling and Preprocessing: Proficiency in data preprocessing and cleaning techniques, especially with text data. Knowledge of tokenization, text formatting, and handling large-scale datasets is important.
4. AI Development Tools: Familiarity with AI development tools and frameworks, version control systems (e.g., Git), and collaborative development practices.
5. Problem Solving and Research Abilities: Strong analytical and problem-solving skills, with the ability to understand and apply AI research papers to real-world applications.
6. Continuous Learning: A passion for staying updated with the latest advancements in the AI and NLP domains and willingness to continuously learn and improve skills.
7.Problem Domain Knowledge: Familiarity with the specific domains where GPT models will be applied (e.g., chatbots, language translation, content generation) can be beneficial in understanding the context and requirements of the projects.
Role: Full Stack Developer
Industry Type: IT Services & Consulting
Department: Engineering - Software & QA
Employment Type: Full Time, Permanent
Role Category: Software Development
Education
UG: B.Tech/B.E. in Computers, Electrical
