Data Scientist

• Design, build and deploy scalable and robust production-ready solutionswith large language models (LLMs) for automation and advanced AI applications. Such solutions can be APIs and web-based applications (typically containerised applications), to integrate models into business workflows.
• Implement and manage LLMOps/MLOps workflows to ensure reliable deployment, monitoring, and lifecycle management of large language models.
• This includes setting up automated pipelines for model versioning, performance tracking, drift detection, and continuous evaluation against business KPIs, while integrating observability tools for real-time health checks and compliance.
• Develop and maintain data pipelines and CI/CD/CT workflows for model training, evaluation, and real-time inference.
• Analyse structured and unstructured data to extract meaningful insights and support strategic decision-making for business
• Collaborate closely with cross-functional teams, including software engineers, product managers, and business stakeholders, to deliver end-to-end solutions.
• Communicate findings and recommendations through clear reports, dashboards, and presentations.
• Work seamlessly with UK-based teams, ensuring clear communication and alignment across time zones.

Requirements

• Strong programming skills in Python (including best practices for clean, maintainable code); familiarity with web frameworks (e.g., Flask, FastAPI, or Django).
• Proficiency in containerisation and orchestration tools
• Familiarity with LLM fine-tuning, prompt engineering, agentic frameworks and solution deployment using modern framework (e.g., LangGraph, LangChain)
• Expertise in data processing and transformation using Pandas, NumPy, and SQL (ideally PySpark).
• Ability to translate business problems into scalable, production-grade solutions.
• Excellent communication and collaboration skills, with the ability to work effectively in an off-shore setting and maintain strong relationships with UK- based teams.
• Ability to work in a fast-paced environment and manage multiple projects simultaneously.
• Bachelors or Masters degree in Computer Science, Data Science, Statistics, or a related field.
• 3+ years of experience in software engineering, data science, machine learning,vor AI engineering.
• Hands-on experience in developing and deploying GenAI / LLM applications in production environments, including containerisation and CI/CD pipelines.
• Exposure to cloud platforms (ideally Azure and Databricks)
• (Bonus) Experience working with large-scale datasets and distributed computing (Spark or similar).