The Sales Intern will assist the sales team in lead generation, client communication, and market research. This role is designed to provide hands-on exposure to the full sales cycle while helping the intern build key skills in communication, sales strategy, and CRM tools. The goal is to support business development while preparing the intern for a successful career in sales. MBA With Agriculture background. Freshers are welcome to apply. Key Responsibilities Research and identify potential leads and clients Assist in client outreach and follow-ups via email and phone Help manage and update CRM data Support the preparation of sales presentations and proposals Participate in team meetings and brainstorming sessions Key Skills & Competencies Strong communication & interpersonal skills Client-focused approach with a solution-oriented mindset Excellent networking and relationship management abilities Eagerness to learn and contribute in a fast-paced environment Basic knowledge of sales principles and customer service practices Proficiency in Malayalam,English and Hindi is required. Real-world experience in sales and client management Exposure to CRM systems and sales tools Internship certificate upon successful completion Opportunity for a full-time role based on performance

B.Sc. or M.Sc. in Agriculture, Food Technology, Geoinformatics, or related fields. Job Skills Required Proficiency in Microsoft Excel for data entry, organization, and basic analysis. Strong communication skills, both written and verbal. Understanding of agricultural conditions, preferably in plantation crops like coffee. Basic knowledge of GIS tools or mobile apps for geolocation and polygon mapping. Ability to work independently in the field Team player with a willingness to contribute actively during team discussions. Job Responsibilities Conduct farm visits in coffee-growing regions to collect geospatial data. Draw and document field polygons using mobile or GIS-based tools. Maintain and organize data records accurately in Excel. Assist in preparatory and brainstorming sessions with the project team. Support the main team in project coordination and follow-up activities. Travel extensively in rural and hilly coffee plantation zones. Benefits Hands-on experience in sustainable agriculture and field-based research. Exposure to geospatial mapping techniques in real-world settings. Opportunity to work with an experienced and multidisciplinary team. Certificate of internship and letter of recommendation based on performance. Field travel reimbursement as per organizational policy. Mentorship and learning opportunities in sustainability and rural development

Job Summary We are looking for a passionate and technically skilled AI Intern to support our AI/ML initiatives. This role offers hands-on experience in building intelligent systems, working with datasets, and contributing to innovative AI solutions. Qualification Bachelors Degree in Computer Science,IT, AI, ML or a related field. Technical Skills Required Programming Languages: Proficiency in Python; familiarity with R, Java, or C++ is a plus. Machine Learning Libraries: scikit-learn, XGBoost, LightGBM. Deep Learning Frameworks: TensorFlow, PyTorch, Keras. Data Handling: pandas, NumPy, SQL, Apache Spark (basic). Data Visualization: Matplotlib, Seaborn, Plotly. Natural Language Processing (NLP): spaCy, NLTK, Hugging Face Transformers. Computer Vision (optional): OpenCV, torchvision. Model Deployment: Flask/FastAPI, Docker, basic understanding of REST APIs. Version Control: Git, GitHub/GitLab. Cloud Platforms (preferred): AWS (SageMaker) or Azure ML. Tools Environments: Jupyter Notebooks, VS Code, Google Colab. Familiarity with MLOps concepts and tools (e.g., Kubeflow , Docker , Kubernetes , MLflow , DVC) is a bonus. Strong foundation in statistics, linear algebra, and probability. Job Responsibilities Assist in developing, training, and evaluating machine learning and deep learning models. Perform data preprocessing, feature engineering, and exploratory data analysis (EDA). Support the deployment and monitoring of AI models in production environments. Conduct research on state-of-the-art AI techniques and present findings. Collaborate with cross-functional teams to integrate AI solutions into products. Document code, experiments, and project outcomes clearly and concisely.