
AI/ML Engineer – Intern/Fresher/Experienced
2 weeks ago
Location: Vadodara
Type: Full-time / Internship
Duration (for interns): Minimum 3 months
Stipend/CTC: Based on experience and role
About Gururo
Gururo is an industry leader in practical, career-transforming education. With a mission to empower professionals and students through real-world skills, we specialize in project management, leadership development, and emerging technologies. Join our fast-paced, mission-driven team and work on AI/ML-powered platforms that impact thousands globally.
Who Can Apply?
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Interns: Final-year students or recent graduates from Computer Science, Data Science, or related fields, with a strong passion for AI/ML.
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Freshers: 0–1 years of experience with academic or internship exposure to machine learning projects.
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Experienced Professionals: 1+ years of hands-on experience in AI/ML roles with a demonstrated portfolio or GitHub contributions.
Key Responsibilities
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Design and develop machine learning models and AI systems for real-world applications
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Clean, preprocess, and analyze large datasets using Python and relevant libraries
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Build and deploy ML pipelines using tools like Scikit-learn, TensorFlow, PyTorch
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Work on NLP, Computer Vision, or Recommendation Systems based on project needs
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Evaluate models with appropriate metrics and fine-tune for performance
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Collaborate with product, engineering, and design teams to integrate AI into platforms
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Maintain documentation, participate in model audits, and ensure ethical AI practices
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Use version control (Git), cloud deployment (AWS, GCP), and experiment tracking tools (MLflow, Weights & Biases)
Must-Have Skills
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Strong Python programming skills
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Hands-on experience with one or more ML frameworks (Scikit-learn, TensorFlow, or PyTorch)
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Good understanding of core ML algorithms (classification, regression, clustering, etc.)
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Familiarity with data wrangling libraries (Pandas, NumPy) and visualization (Matplotlib, Seaborn)
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Experience working with Jupyter Notebooks and version control (Git)
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Basic understanding of model evaluation techniques and metrics
Good to Have (Optional)
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Exposure to deep learning, NLP (transformers, BERT), or computer vision (OpenCV, CNNs)
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Experience with cloud ML platforms (AWS SageMaker, GCP AI Platform, etc.)
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Familiarity with Docker, APIs, and ML model deployment workflows
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Knowledge of MLOps tools and CI/CD for AI systems
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Kaggle profile, published papers, or open-source contributions
What You’ll Gain
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Work on real-world AI/ML problems in the fast-growing EdTech space
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Learn from senior data scientists and engineers in a mentorship-driven environment
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Certificate of Internship/Experience & Letter of Recommendation (for interns)
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Opportunities to lead research-driven AI initiatives at scale
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Flexible work hours and performance-based growth opportunities
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End-to-end exposure — from data collection to model deployment in production
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