Job Title

We are seeking an experienced and highly motivated Data Scientist with a strong background in backend development and AI/ML engineering. The ideal candidate will have solid experience in building, deploying, and scaling machine learning solutions using Python and modern ML frameworks. Key Responsibilities: Design, develop, and deploy machine learning models, including advanced architectures such as Large Language Models (LLMs). Collaborate with cross-functional teams to build scalable AI-driven solutions using robust software engineering principles. Leverage Python and object-oriented programming techniques to create efficient, maintainable, and production-grade ML pipelines. Work with popular machine learning frameworks such as TensorFlow , PyTorch , and Scikit-learn for model development and experimentation. Integrate AI/ML models into applications using RESTful APIs and ensure performance, scalability, and reliability. Utilize tools such as Hugging Face , LangChain , and OpenAI APIs to build and fine-tune NLP and generative AI models. Implement and manage containerized services using Docker , enabling smooth deployment and reproducibility of ML solutions. Apply best practices in version control (Git) and software development lifecycles to support collaborative and agile workflows. Design, develop, and maintain relational databases (e.g., MySQL , PostgreSQL , Oracle ) to support data-driven applications. Contribute to the design and implementation of microservices-based architectures for AI/ML systems. Understand and apply agent communication protocols and multi-agent system design (e.g., MCP) where relevant to AI applications. Analyze large datasets, derive actionable insights, and drive continuous model improvements. Required Skills and Qualifications: 4+ years of experience in data science, machine learning, or backend development roles. Proficiency in Python and strong foundations in object-oriented programming . Hands-on experience with machine learning model lifecycle — from training to production deployment and monitoring. Familiarity with scalable system design and microservices architecture. Excellent problem-solving skills, attention to detail, and a strong understanding of data structures and algorithms. Effective communication and collaboration skills, with the ability to work in a dynamic team environment. Preferred Qualifications: Generative AI Expertise: Practical experience and in-depth knowledge of Generative AI technologies, including Large Language Models (LLMs) such as GPT, LLaMA, and their real-world applications. Prompt Engineering & Model Optimization: Proficiency in prompt engineering, fine-tuning LLMs, and evaluating the performance and effectiveness of AI/ML models. AI System Architecture: Familiarity with orchestration frameworks and agent-based system architectures for building modular and intelligent AI solutions. Advanced AI Tooling: Experience working with and integrating state-of-the-art AI tools, platforms, and APIs into scalable systems. Innovation Mindset: Demonstrated ability to creatively apply AI/ML — including Generative AI and LLMs — to solve complex problems and deliver business value, especially in the payment technology or fintech domains. Cross-Functional Collaboration: Strong communication skills with a proven track record of working effectively in cross-disciplinary teams, including product, engineering, and data stakeholders. Responsible AI Practices: Knowledge of ethical AI principles, including model interpretability, fairness, responsible AI deployment, and ongoing model monitoring.