Data Scientist (Python)

- Design, build, and deploy scalable production-ready solutions using Large Language Models (LLMs) for automation and advanced AI applications. - Develop APIs and containerized web-based applications to integrate AI models into business workflows. - Implement and manage LLMOps/MLOps pipelines for model deployment, monitoring, and lifecycle management. - Set up automated workflows for model versioning, performance tracking, drift detection, and continuous evaluation against business KPIs. - Integrate observability tools to enable real-time monitoring, system health checks, and compliance management. - Develop and maintain data pipelines and CI/CD/CT workflows for model training, evaluation, and real-time inference. - Analyze structured and unstructured data to generate insights and support strategic decision-making. - Collaborate with software engineers, product managers, and business stakeholders to deliver end-to-end AI solutions. - Communicate analytical findings and recommendations through reports, dashboards, and presentations. - Work closely with UK-based teams to ensure smooth collaboration and alignment across time zones. Required Skills & Abilities - Strong programming expertise in Python with focus on clean, maintainable, and scalable code. - Familiarity with web frameworks such as Flask, FastAPI, or Django. - Proficiency in containerization and orchestration tools (e.g., Docker, Kubernetes). - Experience with LLM fine-tuning, prompt engineering, and agent-based AI frameworks. - Hands-on experience with modern GenAI frameworks such as LangGraph or LangChain. - Strong expertise in data processing using Pandas, NumPy, and SQL. - Experience working with large-scale data processing frameworks such as PySpark. - Ability to translate complex business problems into scalable AI-driven solutions. - Strong communication and collaboration skills, particularly when working with distributed teams. - Ability to work in fast-paced environments while managing multiple projects simultaneously. Qualifications & Experience - Bachelor's or Master's Degree in Computer Science, Data Science, Statistics, or a related field. - Minimum 3+ years of experience in software engineering, data science, machine learning, or AI engineering roles. - Hands-on experience developing and deploying Generative AI / LLM applications in production environments. - Experience implementing containerized deployments and CI/CD pipelines for AI applications. - Exposure to cloud platforms such as Microsoft Azure and Databricks. - Bonus: Experience working with large-scale datasets and distributed computing frameworks such as Apache Spark. Originally posted on Himalayas