Trainee Engineer

About the Role

We are looking for a motivated and technically capable Trainee Engineer with strong Python programming skills and an interest in Machine Learning, Deep Learning, and Scientific Computing. The candidate will work closely with our R&D team on developing computational models, implementing algorithms, processing datasets, and integrating software components into functional systems. We are particularly interested in candidates who possess strong programming fundamentals, practical problem-solving abilities, and a willingness to learn new technologies. Initial technical guidance and mentorship will be provided, with opportunities to progressively take ownership of assigned tasks and projects.

Key Responsibilities

• Develop, debug, test, and maintain Python-based applications and computational workflows.
• Implement, train, evaluate, and optimize Machine Learning and Deep Learning models.
• Perform data preprocessing, analysis, visualization, and dataset management.
• Translate technical specifications, algorithms, and research methodologies into working Python implementations.
• Assist in integrating ML models, software modules, APIs, and automated workflows.
• Conduct assigned experiments, troubleshoot implementation issues, and document results.
• Support projects involving scientific computing, numerical methods, signal processing, and research applications.
• Assist in developing and integrating LLM/SLM-based applications, learning relevant frameworks and tools as required.
• Collaborate with the R&D team to test, improve, and integrate software solutions.

Requirements & Tech Stack

• Strong proficiency in Python programming, including data structures, functions, object-oriented programming, and debugging.
• Practical knowledge of NumPy, Pandas, and Matplotlib, with basic familiarity with SciPy.
• Fundamental understanding of Machine Learning, Deep Learning, and Neural Networks.
• Familiarity with at least one deep-learning framework, preferably PyTorch or TensorFlow/Keras.
• Ability to understand technical requirements and translate them into functional code.
• Basic knowledge of algorithms, software development practices, and version control using Git.
• Basic familiarity with Linux environments.
• Good analytical thinking, problem-solving abilities, and willingness to learn independently.
• Ability to communicate technical progress and document implementation results.

Preferred Skills

• Exposure to deep-learning architectures such as CNNs, GNNs, or Graph Attention Networks (GATs).
• Familiarity with LLMs, SLMs, Generative AI, Hugging Face, Retrieval-Augmented Generation (RAG), fine-tuning, or local model inference.
• Knowledge of numerical computing, mathematical modelling, signal processing, or scientific programming.
• Experience with APIs, databases, GUI development, or workflow automation.
• Interest in physics-informed machine learning, computational physics, or scientific instrumentation.
• Experience implementing technical projects, research papers, or computational algorithms through academic or personal projects.

Educational Qualifications

B.E./B.Tech./M.E./M.Tech./M.Sc. in:

• Computer Science / Information Technology
• Artificial Intelligence / Machine Learning / Data Science
• Electronics and Communication Engineering
• Electrical / Electronics Engineering
• Physics / Applied Physics
• Mathematics / Applied Mathematics
• Or related technical disciplines

Fresh graduates and candidates with relevant academic projects, internships, or practical programming experience are encouraged to apply.