Graduate Engineer Trainee

About Company :

Larsen & Toubro is an Indian multinational engaged in EPC Projects, Hi-Tech Manufacturing and Services. It operates in over 50 countries worldwide. A strong, customer-focused approach and the constant quest for top-class quality have enabled L&T to attain and sustain leadership in its major lines of business for over eight decades. Corporate Sustainability:

L&T was the first company in India in the engineering & construction space to publicly disclose its sustainability performance. Our Integrated Report, which tracks the sustainability performance of the organisation and its inter-connectedness with the financial performance, showcases how L&T is adding value to its stakeholders.

Job Description :

As a Machine Learning Intern, you will work alongside a team of data scientists and engineers to develop, implement, and optimize machine learning algorithms and models. This job offers the opportunity to build practical skills in data analysis, machine learning, and software engineering while contributing to impactful projects within the company.

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We are searching for a dependable graduate engineer trainee to join our capable team. The graduate engineer trainee will be responsible for completing all tasks assigned by the supervisor, assisting other engineers with projects, conducting research, and writing reports. You should be able to follow instructions, but also take initiative and come up with original ideas.

Role & Responsibility :

• Develop & Assist in the design, development, and testing of machine learning models and algorithms.
• Conduct data preprocessing, feature engineering, and data analysis to prepare datasets for modeling.
• Collaborate with cross-functional teams to understand business needs and apply machine learning techniques to solve real-world problems.
• Help in model evaluation, performance tuning, and optimization.
• Write and maintain clean, efficient, and well-documented code.
• Contribute to research on emerging machine learning techniques and tools.
• Prepare and present findings, reports, and visualizations for technical and non-technical stakeholders.

Required Skills :

• Strong understanding of machine learning concepts and algorithms (e.g., regression, classification, clustering, neural networks, etc.).
• Proficiency in programming languages such as Python, R, or similar.
• Experience with machine learning libraries and frameworks (e.g., TensorFlow, Keras, scikit-learn, PyTorch).
• Solid understanding of data structures, algorithms, and problem-solving techniques.
• Familiarity with data preprocessing, feature engineering, and model evaluation techniques.
• Strong analytical, problem-solving, and communication skills.
• Ability to work both independently and collaboratively in a fast-paced environment.

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Preferred Skills (optional):

• Experience with deep learning techniques and frameworks.
• Familiarity with cloud platforms (e.g., AWS, Google Cloud, Azure).
• Knowledge of version control tools (e.g., Git).
• Experience with SQL and working with databases.