Senior Python Developer
2 days ago
Looking for Senior Python Developer
Mode - Work from Office
No of Days 5 days of working
Shift Timing 2.00PM to 11.00PM
Roles and Responsibilities
- Develop machine learning models to solve specific business problems.
- Collaborate with data scientists to fine-tune algorithms and improve accuracy.
- Deploy ML models into production environments using frameworks like Django.
- Write clean, maintainable code in Python, focusing on AI and ML development.
- Work with large datasets to train machine learning models.
- Implement APIs in Django for serving predictions made by ML models.
- Analyse and interpret complex data to derive insights and support decision-making.
- Design and implement machine learning models to analyse trends and patterns.
- Use Django to build data-driven applications that visualize results.
- Develop and maintain AI models and systems that help automate tasks.
- Work on natural language processing, computer vision, or other AI subfields.
- Use Django to create user interfaces for AI model interactions.
- Build end-to-end applications, integrating front-end and back-end technologies.
- Implement machine learning and AI features in web applications built with Django.
- Ensure that applications are scalable and maintainable.
- Manage the deployment and scaling of machine learning models in production.
- Use containerization (e.g., Docker) and orchestration tools (e.g., Kubernetes) for AI solutions.
- Monitor and optimize resource usage for machine learning applications built with Django.
- Use Django to create RESTful APIs for accessing ML model predictions and integrating with other systems.
- Implement testing strategies to ensure the quality and performance of algorithms and applications.
- Collaborate with data scientists to fine-tune algorithms and improve accuracy.
- Write clean, maintainable code in Python, focusing on AI and ML development.
- Proficiency in Python, as well as familiarity with frameworks like Django for web development.
- Understanding of machine learning concepts, algorithms, and best practices.
- Experience with data libraries such as Pandas, NumPy, and visualization tools like Matplotlib or Seaborn.
- Familiarity with Git for version control.
- Knowledge of deployment techniques and cloud platforms (e.g., AWS, Google Cloud) for hosting applications.
- Strong communication skills to help convey technical details to non-technical stakeholders of Form
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