Application Developer

Design, develop solutions, and fine-tune cutting-edge generative AI models, including open-source LLMs, for real-world, scalable applications. Apply NLP techniques for tasks like text generation, summarization, translation, entity recognition, and sentiment analysis using frameworks like Hugging Face, spaCy, and OpenAI GPT. Design and implement scalable end-to-end applications integrating AI models using modern front-end (React, Angular, etc.) and back-end (FastAPI, Django, Node.js) technologies. Leverage Python for both AI algorithm development and backend services, ensuring seamless integration between machine learning models and application logic. Apply supervised, unsupervised, and reinforcement learning techniques using libraries such as Scikit-learn, TensorFlow, and PyTorch. Customize pre-trained models with domain-specific data, improving accuracy and efficiency in inference workflows. Build and manage robust MLOps pipelines including Docker, Kubernetes, and CI/CD for continuous deployment, monitoring, and model management. Develop AI-powered virtual assistants using LangChain, AutoGen, or similar libraries to meet enterprise conversational requirements. Deploy and scale applications using cloud platforms such as Azure, or AWS for secure, high-performance model hosting. Collaborate with data engineers to process and manage large datasets with tools like Apache Spark, Pandas, and SQL for training and evaluation. Build RESTful APIs to expose AI capabilities and enable seamless integration with business systems and UI components. Stay updated with the latest trends in generative AI and contribute to open-source AI projects to stay ahead in innovation and design. Awareness of ethical AI design and practices to ensure responsible AI deployments and fair model behavior in production environments.

Strong experience in Generative AI & Large Language Models (LLM). Proficiency in Natural Language Processing (NLP). Experience in Full Stack Development. Strong Python programming skills for AI & Web Applications. Knowledge of Machine Learning & Deep Learning techniques. Experience with MLOps & Production-Ready AI Deployment.

Experience with Conversational AI & Chatbot Frameworks. Familiarity with Cloud AI Platform Integration. Knowledge of Data Engineering & Preprocessing. Experience in API Development & Integration. Interest in AI Research, Innovation & Open-Source Contribution. Understanding of AI Ethics & Bias Mitigation.

Inclusive recruitment process valuing diverse backgrounds and experiences.