Data Scientist

As a skilled and motivated Data Scientist with a strong background in backend development and AI/ML engineering, you will be responsible for developing, implementing, and expanding machine learning solutions using Python and modern ML frameworks. Your key responsibilities will include: - Developing and implementing machine learning models, such as Large Language Models (LLMs). - Collaborating with various teams to create scalable AI-driven solutions using sound software engineering principles. - Utilizing Python and object-oriented programming to build efficient, maintainable, and production-grade ML pipelines. - Working with popular ML frameworks like TensorFlow, PyTorch, and Scikit-learn for model development and testing. - Integrating AI/ML models into applications via RESTful APIs to ensure performance, scalability, and reliability. - Using tools like Hugging Face, LangChain, and OpenAI APIs for NLP and generative AI model development. - Managing containerized services using Docker for seamless deployment and reproducibility of ML solutions. - Following best practices in version control (Git) and software development lifecycles to support collaborative and agile workflows. - Developing and maintaining relational databases to support data-driven applications. - Contributing to microservices-based architectures for AI/ML systems. - Applying agent communication protocols and multi-agent system design in relevant AI applications. - Analyzing large datasets, extracting actionable insights, and continuously improving models. Required Skills and Qualifications: - Minimum 4 years of experience in data science, machine learning, or backend development. - Proficiency in Python and solid foundations in object-oriented programming. - Hands-on experience with the entire machine learning model lifecycle. - Understanding of scalable system design and microservices architecture. - Strong problem-solving skills, attention to detail, and knowledge of data structures and algorithms. - Excellent communication and collaboration abilities, with a knack for working in a dynamic team setting. Preferred Qualifications: - Expertise in Generative AI, particularly with Large Language Models (LLMs) like GPT and LLaMA. - Proficiency in prompt engineering, fine-tuning LLMs, and evaluating AI model performance. - Familiarity with AI system architecture, including orchestration frameworks and agent-based designs. - Experience with advanced AI tools, platforms, and APIs for scalable systems. - Strong communication skills and proven track record of effective collaboration in cross-disciplinary teams. - Knowledge of ethical AI principles, including model interpretability, fairness, responsible AI deployment, and ongoing monitoring.,