As an AI Intern at Quest Global, you will be part of a highly specialized engineering group focused on exploring and executing R&D activities for advanced energy projects. Your primary technical mandate will involve writing clean, optimized automation scripts and data manipulation logic using Python . You will participate actively in building, testing, and fine-tuning intelligent prototypes using open-source machine learning models and modern foundational frameworks.
You will leverage your analytical reasoning to structure raw technical information, create robust backend integrations, and maintain data pipeline reliability. Working alongside senior developers, you will implement tools that incorporate Large Language Models (LLMs) or predictive algorithms to optimize energy efficiency and grid diagnostics. This role requires an individual who can apply core computer science fundamentals directly to real-world deployment challenges, bridging the gap between innovative research and enterprise-scale execution.
Key Responsibilities
Contribute directly to AI/ML development and investigative R&D activities for upcoming energy projects.
Write maintainable, efficient code blocks using Python and backend frameworks.
Integrate machine learning solutions seamlessly with legacy or cloud-native platform architectures.
Utilize deep learning libraries to preprocess, cleanse, and structure large datasets.
Experiment with and implement agentic workflows using LangChain or Hugging Face .
Participate in peer code reviews, sprint documentation, and internal technical discussions.
Apply object-oriented design patterns to optimize backend application layers.
Collaborate across cross-functional global teams to deliver high-integrity software components.
Skills & Eligibility
Education: Bachelor’s or Master’s degree in Computer Science, IT, Data Science, or related engineering domains.
Programming: Mandatory proficiency in Python . Knowledge of JavaScript or Java is a major advantage.
CS Foundations: Strong command over Data Structures, Algorithms (DSA) , and OOP concepts.
AI/ML Frameworks: Foundational familiarity with PyTorch, TensorFlow, Scikit-Learn, LangChain, or Hugging Face.
Analytical Mindset: Strong critical thinking and the ability to break complex problems into logical pieces.
Traits: Highly motivated, self-driven, excellent verbal and written communication skills, and an eager learner.
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