AI/ML Intern
Voreva
IndiaFresher3h agovia LinkedIn
This job at a glance
- Who can apply
- Freshers and up to 1 year
- Must know
- Machine learningPythonData structures & algorithmsData analysisTroubleshootingscikit-learn
- Nice to have
- Deep learningPyTorchTensorFlowREST APIs
- Work
- On-site in India · internship
- Pay
- Not stated by the employer.
- Skill demand
- Machine learning84%Python71%Data structures & algorithms20%Data analysis14%of 99 similar fresher jobs posted in India this week
- Listed
- 31 Oct 2026 · still open
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About the Role
We are seeking an enthusiastic AI/ML Intern to assist in designing, training, and deploying data-driven machine learning models and AI solutions.
Key Responsibilities
- Assist in developing, training, testing, and deploying machine learning models.
- Collect, clean, preprocess, and analyze structured and unstructured datasets.
- Implement machine learning algorithms using Python and relevant libraries.
- Conduct exploratory data analysis to identify patterns, trends, and insights.
- Evaluate model performance using appropriate metrics such as accuracy, precision, recall, and F1-score.
- Assist in optimizing models to improve accuracy, efficiency, and reliability.
- Support the development of AI-powered applications, chatbots, recommendation systems, and predictive models.
- Research emerging AI/ML technologies, frameworks, tools, and industry developments.
- Debug code, troubleshoot technical issues, and assist in model validation.
- Collaborate with developers, data scientists, and other team members on AI/ML projects.
- Document experiments, methodologies, model results, and technical findings.
- Follow responsible AI practices, including data privacy, quality, and bias awareness.
Requirements & Qualifications
- Pursuing or recently completed a degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, or a related field; equivalent practical skills may also be considered.
- Knowledge of Python programming is must.
- Understanding of fundamental machine learning concepts, including supervised and unsupervised learning.
- Familiarity with libraries such as NumPy, Pandas, and Scikit-learn.
- Basic knowledge of statistics, probability, and linear algebra.
- Basic knowledge of Git and GitHub for version control is beneficial.
- Familiarity with deep learning frameworks such as TensorFlow or PyTorch is an advantage.
- Exposure to generative AI, large language models (LLMs), or API integration is desirable.
- Strong analytical thinking, problem-solving, and debugging skills.
- Good communication skills and the ability to collaborate effectively in a team.