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: 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