AI/ML Engineer ?? Intern/Fresher/Experienced

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
Interns: Final-year students or recent graduates from Computer Science, Data Science, or related fields, with a strong passion for AI/ML, Freshers: 01 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 Youll 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
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