ML Intern

Machine Learning Intern Location: Bangalore (Onsite) Duration: Semester Internship (Full-time commitment) Company: London Stock Exchange Group Role Overview We are seeking a highly motivated Machine Learning Intern to join Emerging Tech PoC Team within Data and Analytics operations function of the London Stock Exchange Group (LSEG). This is an exciting opportunity to contribute to applied research and innovation in the fields of Generative AI, Information Retrieval, and Information Extraction. As part of this role, you will assist in building end-to-end machine learning pipelinesfrom research and development to deployment and scalingwhile gaining exposure to the latest advancements in AI technologies. You will collaborate with a team of experts to deliver cutting-edge solutions, leverage state-of-the-art tools, and work on real-world data at scale. This internship provides an excellent opportunity for hands-on experience in a fast-paced, dynamic environment where you will be encouraged to think critically, explore innovative ideas, and make impactful contributions. Key Responsibilities Assist in designing, building, and deploying scalable ML pipelines. Explore and implement state-of-the-art frameworks in Machine Learning (e.g., TensorFlow, PyTorch) and Generative AI (e.g., LangChain, LangGraph, LlamaIndex). Conduct research on the latest advancements in AI and apply them to solve real-world problems. Develop prototypes and Proof of Concepts (PoCs) to validate new ideas and solutions. Collaborate with cross-functional teams to deliver innovative AI solutions at scale. Required Skills Technical Expertise: Strong proficiency in Python programming. Knowledge of ML frameworks such as TensorFlow and PyTorch. Brownie points for familiarity with Generative AI frameworks like LangChain, LangGraph, and LlamaIndex . Understanding of ML algorithms like regression, classification, transformers, and neural networks. Soft Skills: Strong problem-solving and critical-thinking abilities. Eagerness to learn and innovate with out-of-the-box approaches. Excellent communication skills, a team player, and confidence in presenting ideas. Education Currently pursuing a B.Tech with specialization in Data Science or a related field from a Tier-1 institution. Demonstrates expertise in Python programming and a strong foundation in data science concepts.

London Stock Exchange Group (LSEG) is a global leader in financial markets infrastructure and data services, enabling businesses and economies worldwide to thrive. At the intersection of technology and finance, LSEG offers dynamic opportunities to innovate and impact global markets. As part of the PoC team, you will be contributing to cutting-edge AI applications in financial technology, working with diverse datasets to solve complex challenges. LSEG is a leading global financial markets infrastructure and data provider. Our purpose is driving financial stability, empowering economies and enabling customers to create sustainable growth. Our purpose is the foundation on which our culture is built. Our values of Integrity, Partnership, Excellence and Change underpin our purpose and set the standard for everything we do, every day. They go to the heart of who we are and guide our decision making and everyday actions. Working with us means that you will be part of a dynamic organisation of 25,000 people across 65 countries. However, we will value your individuality and enable you to bring your true self to work so you can help enrich our diverse workforce. You will be part of a collaborative and creative culture where we encourage new ideas and are committed to sustainability across our global business. You will experience the critical role we have in helping to re-engineer the financial ecosystem to support and drive sustainable economic growth. Together, we are aiming to achieve this growth by accelerating the just transition to net zero, enabling growth of the green economy and creating inclusive economic opportunity. LSEG offers a range of tailored benefits and support, including healthcare, retirement planning, paid volunteering days and wellbeing initiatives.