AI/ML Engineer – Intern/Fresher/Experienced

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Type:

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About Gururo

Who Can Apply?

• Interns: Final-year students or recent graduates from Computer Science, Data Science, or related fields, with a strong passion for AI/ML.
• Freshers: 0–1 years of experience with academic or internship exposure to machine learning projects.
• Experienced Professionals: 1+ years of hands-on experience in AI/ML roles with a demonstrated portfolio or GitHub contributions.
  

Key Responsibilities

• Design and develop machine learning models and AI systems for real-world applications
• Clean, preprocess, and analyze large datasets using Python and relevant libraries
• Build and deploy ML pipelines using tools like Scikit-learn, TensorFlow, PyTorch
• Work on NLP, Computer Vision, or Recommendation Systems based on project needs
• Evaluate models with appropriate metrics and fine-tune for performance
• Collaborate with product, engineering, and design teams to integrate AI into platforms
• Maintain documentation, participate in model audits, and ensure ethical AI practices
• Use version control (Git), cloud deployment (AWS, GCP), and experiment tracking tools (MLflow, Weights & Biases)
  

Must-Have Skills

• Strong Python programming skills
• Hands-on experience with one or more ML frameworks (Scikit-learn, TensorFlow, or PyTorch)
• Good understanding of core ML algorithms (classification, regression, clustering, etc.)
• Familiarity with data wrangling libraries (Pandas, NumPy) and visualization (Matplotlib, Seaborn)
• Experience working with Jupyter Notebooks and version control (Git)
• Basic understanding of model evaluation techniques and metrics
  

Good to Have (Optional)

• Exposure to deep learning, NLP (transformers, BERT), or computer vision (OpenCV, CNNs)
• Experience with cloud ML platforms (AWS SageMaker, GCP AI Platform, etc.)
• Familiarity with Docker, APIs, and ML model deployment workflows
• Knowledge of MLOps tools and CI/CD for AI systems
• Kaggle profile, published papers, or open-source contributions
  

What You’ll Gain

• Work on real-world AI/ML problems in the fast-growing EdTech space
• Learn from senior data scientists and engineers in a mentorship-driven environment
• Certificate of Internship/Experience & Letter of Recommendation (for interns)
• Opportunities to lead research-driven AI initiatives at scale
• Flexible work hours and performance-based growth opportunities
• End-to-end exposure — from data collection to model deployment in production