AI/ML Engineer – Intern/Fresher/Experienced
- Vadodara, Gujarat
- Training
- Full-time
Type: Full-time / Internship
Duration (for interns): Minimum 3 months
Stipend/CTC: Based on experience and roleAbout GururoGururo 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 ResponsibilitiesDesign and develop machine learning models and AI systems for real-world applicationsClean, preprocess, and analyze large datasets using Python and relevant librariesBuild and deploy ML pipelines using tools like Scikit-learn, TensorFlow, PyTorchWork on NLP, Computer Vision, or Recommendation Systems based on project needsEvaluate models with appropriate metrics and fine-tune for performanceCollaborate with product, engineering, and design teams to integrate AI into platformsMaintain documentation, participate in model audits, and ensure ethical AI practicesUse version control (Git), cloud deployment (AWS, GCP), and experiment tracking tools (MLflow, Weights & Biases)Must-Have SkillsStrong Python programming skillsHands-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 metricsGood 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 workflowsKnowledge of MLOps tools and CI/CD for AI systemsKaggle profile, published papers, or open-source contributionsWhat You’ll GainWork on real-world AI/ML problems in the fast-growing EdTech spaceLearn from senior data scientists and engineers in a mentorship-driven environmentCertificate of Internship/Experience & Letter of Recommendation (for interns)Opportunities to lead research-driven AI initiatives at scaleFlexible work hours and performance-based growth opportunitiesEnd-to-end exposure — from data collection to model deployment in production