Introduction: SymphonyAI is at the forefront of innovation, leveraging cutting-edge artificial intelligence and machine learning technologies to transform industries and drive business growth. As a global leader in AI-powered solutions, we empower organizations to harness the full potential of data-driven insights. SymphonyAI enterprise applications rapidly deliver transformative business value across retail, CPG, financial services, manufacturing, media, Enterprise IT (SymphonyAI Summit) and the public sector. SymphonyAI combines unrivalled AI technology, vertical expertise and industry-specific data and insights into applications that drive the highest value for customers. We are one of the largest and fastest growing AI portfolios. We are on a mission to build a “World Class Team” with a high-performance culture. Job Description: As a Senior Data Scientist, you will lead the design, development, and deployment of advanced machine learning and deep learning solutions across a variety of domains. You will work with large and complex datasets to drive business insights and power innovative AI products, including state-of-the-art Natural LanguageProcessing (NLP) and Generative AI (GenAI) systems. You will collaborate closely with engineering, product management, and business stakeholders to deliver end-to-end data science solutions, from problem definition through scalable deployment. You will play a key role in shaping our AI/ML strategy, leveraging your expertise in Python, ML/DL frameworks, and cloud technologies to deliver best-in-class solutions. - Design, build, and deploy end-to-end machine learning and deep learning models for business-critical applications, with a focus on NLP, text classification, and generative AI use cases. - Lead development and fine-tuning of Large Language Models (LLMs) and implement retrieval-augmented generation (RAG) pipelines. - Utilize LangChain, LangGraph, and LangFlow frameworks to orchestrate LLM applications and workflows. - Apply advanced NLP techniques to solve real-world business problems, including text extraction, summarization, classification, information retrieval, and entity recognition. - Build scalable, production-grade ML pipelines using TensorFlow/PyTorch, and manage model lifecycle, including versioning, monitoring, and retraining. - Design and execute experiments and benchmarks on model performance, data quality, and feature engineering. - Deploy models as robust, secure APIs using Docker and Kubernetes on cloud platforms such as Azure. - Collaborate with data and DevOps engineers to build, optimize, and maintain MLOps workflows and infrastructure. - Work closely with stakeholders to understand requirements and translate business needs into technical solutions. - Stay up-to-date with the latest research in AI, ML, NLP, and GenAI, and identify opportunities for innovation and improvement. - Mentor and guide junior data scientists, promoting best practices in coding, experimentation, and documentation. - 6+ years of hands-on experience in data science, with strong expertise in Python and its libraries (NumPy, pandas, scikit-learn,Pytorch etc.). - Deep knowledge of core machine learning and deep learning algorithms and architectures. - Demonstrated experience (1+ years) working with Generative AI technologies, including LLMs, fine-tuning, and RAG. - Hands-on experience with NLP techniques and frameworks (spaCy, Hugging Face Transformers, NLTK, etc.). - Extensive experience in TensorFlow and/or PyTorch, including building and training custom models. - Proven track record of deploying ML solutions at scale using Kubernetes, Docker, and Azure cloud services. - Practical experience with LLM orchestration frameworks such as LangChain, and LangFlow. - Strong understanding of software engineering best practices, version control (git), containerization, and CI/CD for ML. - Familiarity with data engineering concepts and tools for large-scale data processing and feature pipelines. - Excellent communication and stakeholder management skills, with the ability to explain complex technical topics to a broad audience. - Self-motivated, collaborative, and passionate about driving business impact through AI innovation. - Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field; PhD is a plus. - Experience in multi-cloud environments ( Preferably Azure) - Knowledge of model monitoring, explainability, and responsible AI practices. - Publications or contributions to the open-source data science/AI community. About Us: - Work on cutting-edge AI and Generative AI projects - Tackle diverse, real-world challenges across multiple industries - Lead and mentor in a high-performance, innovative team - Use advanced tech stack and modern MLOps tools - Enjoy a collaborative, inclusive, and growth-oriented culture We're excited about the possibility of having you join our team and contribute to our mission.