Full Stack Developer (Python & JavaScript) – AI Experience

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Python Full Stack Developer#26-03428

Onsite

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Job Description

• Full Stack Developer (Python & JavaScript) – AI Experience
• Location: Remote
• Employment Type: Full-time
• Experience Required: 8-10 years
• Job Summary
• We are seeking a skilled Full Stack Developer with strong experience in Python, JavaScript, and AI/ML-driven applications. The ideal candidate will design, develop, and maintain scalable web applications while integrating AI capabilities such as machine learning models, data pipelines, or LLM-based features into production systems.
• Key Responsibilities
• Design, develop, and maintain full-stack web applications using Python and JavaScript
• Build and optimize backend services using frameworks such as Django, Flask, or FastAPI
• Develop frontend interfaces using React, Next.js, Vue.js, or Angular
• Integrate AI/ML models into applications (prediction APIs, NLP, recommender systems, chatbots, etc.)
• Work with RESTful APIs and GraphQL for data exchange
• Collaborate with data scientists to deploy and monitor ML models in production
• Optimize application performance, scalability, and security
• Write clean, maintainable, and testable code
• Participate in code reviews and system design discussions
• Deploy and manage applications on cloud platforms(AWS, GCP, Azure)
• Required Skills & Qualifications
• Strong proficiency in Python
• Solid experience with JavaScript (ES6+)
• Frontend frameworks :React / Next.js / Vue / Angular
• Backend frameworks :Django / Flask / FastAPI
• Experience with AI/ML concepts(supervised/unsupervised learning, NLP, LLMs, etc.)
• Hands-on experience with AI libraries such as TensorFlow, PyTorch, Scikit-learn, Hugging Face
• Database experience with PostgreSQL, MySQL, MongoDB
• Familiarity with Docker and CI/CD pipelines
• Understanding of authentication, authorization, and security best practices
• Preferred Skills
• Experience with LLMs, ChatGPT/OpenAI APIs, LangChain, vector databases (Pinecone, FAISS, Weaviate)
• Knowledge of MLOps tools(MLflow, Airflow, Kubeflow)
• Experience with microservices architecture
• Exposure to cloud-native services and serverless computing
• Knowledge of data visualization and analytics tools