Job
Description
Experience: 5 to 10 years Location: Hyderabad Position: Permanent Key Responsibilities: Design and implement AI-driven solutions using Python, integrating machine learning models into scalable web applications. Develop, test, and maintain robust backend services with frameworks such as Django, Flask, and Fast API. Build interactive and responsive front-end interfaces using modern JavaScript frameworks (React/Angular/Vue.js). Integrate AI and machine learning algorithms into full-stack applications, ensuring optimal performance and accuracy. Collaborate closely with data scientists and AI engineers to understand the technical requirements of AI/ML models and implement them efficiently in the application stack. Work with cloud services (AWS, GCP, Azure) to deploy machine learning models and APIs for scalable production use. Design and implement RESTful APIs and microservices to expose AI models for consumption by other services and users. Troubleshoot and optimize both frontend and backend systems for performance, scalability, and reliability. Ensure the security and privacy of AI data and algorithms, following industry best practices and standards. Participate in code reviews, provide mentorship to junior developers, and share knowledge of best practices in both software development and AI integration. Stay current with developments in AI and full-stack technologies, recommending improvements and innovations as needed. Required Skills & amp; Experience: 3+ years of experience as a Full Stack Developer with strong proficiency in Python. Hands-on experience with AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn) and the integration of models into production applications. Strong experience with backend frameworks like Django, Flask, or FastAPI. Proficiency with front-end technologies such as HTML, CSS, JavaScript (ES6+), and modern JavaScript frameworks (React/Angular/Vue.js). Solid understanding of database management systems, both relational (PostgreSQL, MySQL) and NoSQL (MongoDB, Redis). Experience in building and consuming RESTful APIs. Experience deploying machine learning models to the cloud (AWS, GCP, Azure). Familiarity with containerization technologies like Docker and orchestration platforms (Kubernetes). Understanding of data security practices, particularly in AI and machine learning applications. Knowledge of CI/CD pipelines and DevOps practices for seamless deployment and monitoring. Strong problem-solving skills, with the ability to debug, optimize, and troubleshoot complex systems. Preferred Qualifications: Experience in deploying and scaling AI/ML models in production environments. Knowledge of microservices architecture and cloud-native application design. Familiarity with AI model training, testing, and evaluation frameworks. Experience with big data technologies (Hadoop, Spark) is a plus. Experience in the AI-driven product lifecycle, including model performance evaluation and iteration. Familiarity with automated testing and unit testing in the context of full-stack development.
