UI/UX Design

About the internship Selected intern's day-to-day responsibilities include: ANAI seeks a passionate and creative UI/UX Designer with expertise in Figma, UI; UX Design, Wireframing, and Sketch. Join our dynamic team and take charge of creating exceptional user experiences for our cutting-edge products. Key Responsibilities: 1. Collaborate with cross-functional teams to understand project requirements, user needs, and business objectives. 2. Create intuitive and visually appealing user interfaces through wireframing, prototyping, and user-centered design principles. 3. Develop high-fidelity UI mockups and interactive prototypes using Figma, Sketch, and other industry-standard design tools. 4. Conduct user research, and usability testing, and gather feedback to iterate and improve designs. 5. Ensure consistency in visual elements, typography, and overall branding for a seamless user experience. 6. Collaborate with developers to ensure design implementation and provide design support during the development process. 7. Stay updated with the latest design trends, techniques, and tools to continuously enhance our UI/UX capabilities. Join our team and make a significant impact on the user experience of our products. Bring your creativity, attention to detail, and passion for design to create exceptional experiences for our users. Who can apply Only those candidates can apply who: 1. are available for the work from home job/internship 2. can start the work from home job/internship between 12th Oct'24 and 16th Nov'24 3. are available for duration of 4 months 4. have relevant skills and interests ANAI is an integrated platform product ecosystem with the purpose of democratizing AI. Our platform integrates deep learning (data/text), computer vision, and NLP, making us unique to meet all the AI needs of enterprises. From data ingestion through 130 plus data connectors, and 450 plus unique AI & ML models to responsible and explainable AI, we got it all. We leverage AI to democratize AI, and ML models to simplify machine learning implementation, making it simpler and faster, while ensuring expert levels of accuracy, feature, and transparency.