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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Junior Applied AI & Data Scientist - **Company:** TomNext - **Location:** Greater London, UK - **Experience:** Starter - **Contract:** Internship / Graduate position - **Skills:** Artificial Intelligence, Computer Programming, Information Engineering, Data Transformation, Python (Programming Language), Machine Learning, NumPy, Open Source Technology, Performance Tuning, Blockchain, Tensorflow, Cloud Platform System, Pytorch, Flask (Web Framework), Large Language Models, Prompt Engineering, Apache Spark, Model Validation, Fastapi, Pandas, Kubernetes, Information Technology, Xgboost, Machine Learning Operations, Data Pipelines, Docker, Microservices - **Published:** August 30, 2026 - **Apply:** https://www.collegerecruiter.com/job/2815456063-junior-applied-ai--data-scientist ## About the Role * BSc/MSc (2:1 or above) in Data Science, Computer Science, Statistics, Mathematics, or a related STEM field from a UK university (or global equivalent), with demonstrated applied Data Science/ML experience (e.g., dissertation, industrial placement, internship, or competition project). * Strong programming skills in Python, including experience with frameworks like PyTorch, TensorFlow or JAX. * Experience working with LLMs for applied tasks. * Practical experience with diverse ML models beyond LLMs, such as XGBoost, Decision Trees, and DL architectures like CNNs and RL. * Familiarity with vector databases (e.g. Pinecone, FAISS, Qdrant) and RAG pipelines. * Proficiency in data engineering and preprocessing using Pandas, NumPy or Spark. * Experience deploying ML models or AI agents into production (e.g. via FastAPI, Flask or Vertex AI). * Solid understanding of cloud environments (GCP preferred), microservice architecture and containerized deployment (Docker, Kubernetes). * Curiosity and initiative, you prototype, test, and push code without waiting for instruction. * Has the legal right to work in the UK; visa sponsorship is not available for this role. ## Description * Design, prototype and optimize agentic AI tools that power TomNext's investment analysis and automation. * Integrate and structure diverse data sources to enrich TomNext's AI-driven investment intelligence platform. * Contribute to the operational AI stack, including data pipelines, model evaluation and deployment. * Build and refine production-grade AI solutions using LLM APIs, RAG, MCP and Knowledge Graph technologies. * Collaborate closely with the CTO, data engineers and product team to translate complex investment workflows into intuitive, intelligent systems. * Research and experiment with emerging architectures, fine-tuning methods, and multimodal models to keep TomNext at the frontier of applied AI., * Exposure to agentic AI frameworks (e.g. AutoGPT, CrewAI, LangGraph) or emerging standards such as Model Context Protocol (MCP). * Experience or coursework involving LLM fine-tuning, prompt engineering, or model evaluation. * Familiarity with transformer architectures, embeddings, or instruction-tuning concepts. * Understanding of financial data, investment workflows, or fintech systems. * Exposure to blockchain data, tokenisation frameworks, or on-chain analytics. * Contributions to or interest in open-source ML or AI research projects. * Shape the future of how the world invests in alternative assets through cutting-edge AI, automation and blockchain innovation. * Work side by side with the CTO and founding team, learning directly from experienced engineers and entrepreneurs building at the frontier of AI in finance. * See your work go live fast, operate in a high-trust, high-impact startup where prototypes become production systems in weeks, not quarters. * Experiment with frontier tools and real data, contribute to research, and grow your technical depth in a company that values creativity, precision, and execution. * Join a mission-driven, well-funded startup backed by top investors, fintech founders, and senior figures in global financial services. ## Related Videos - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Vectorize all the things! 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