Makunai Global Latest Hiring For AI/ML Engineer Intern | 0-6 months Exp Require Internship

Makunai Global Latest Hiring For AI/ML Engineer Intern | 0-6 months Exp Require. This is a great opportunity for freshers and early-career professionals looking to kickstart their journey in a global IT services company. The position is based in  India and eligible candidates are encouraged to apply online at the earliest. The detailed eligibility criteria and application process are given below. Also Check course section free 

About Company :

Job Description :

Key Responsibilities:

1. Build, train, and evaluate machine learning models for various use cases such as prediction, classification, and recommendation systems.
2. Work with large datasets to clean, preprocess, and transform data for model training.
3. Implement and experiment with algorithms using libraries like Scikit-learn, TensorFlow, or PyTorch.
4. Assist in deploying ML models into production environments using APIs or batch pipelines.
5. Collaborate with engineering teams to integrate ML solutions into product workflows.
6. Perform exploratory data analysis (EDA) and visualize insights using tools like Pandas, Matplotlib, or Seaborn.
7. Optimize model performance through tuning, feature engineering, and validation techniques.
8. Stay updated with the latest advancements in AI/ML and suggest improvements to existing systems.
9. Document experiments, models, and workflows for reproducibility and collaboration.
10. Participate in Agile ceremonies including sprint planning, reviews, and retrospectives.

Required Skills and Qualifications:

1. Bachelor’s degree (or currently pursuing) in Computer Science, Engineering, Data Science, or a related field.
2. 0–6 months of experience or strong academic/project exposure in machine learning or data science.
3. Strong programming skills in Python.
4. Understanding of machine learning concepts such as supervised and unsupervised learning, regression, classification, and clustering.
5. Familiarity with ML libraries such as Scikit-learn, TensorFlow, or PyTorch.
6. Basic knowledge of data structures, algorithms, and statistics.
7. Experience with data manipulation and analysis using Pandas or NumPy.
8. Knowledge of Git and version control workflows.
9. Strong problem-solving skills and eagerness to learn.

1. Experience with deep learning, NLP, or computer vision projects.
2. Familiarity with SQL and working with relational or NoSQL databases.
3. Exposure to cloud platforms such as AWS, Azure, or GCP.
4. Understanding of MLOps concepts and model deployment pipelines.
5. Experience with data visualization tools like Tableau or Power BI.
6. Participation in hackathons, Kaggle competitions, or open-source projects.

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