Ai Engineer

buscojobs España; Zaragoza; Presencial; EUR 40.000 - 70.000; Jornada completa

Descripción de la vacante

An innovative firm is seeking a Frontend AI Engineer to craft intuitive user interfaces powered by artificial intelligence. In this role, you will collaborate with cross-functional teams to develop responsive web applications that enhance user experiences through AI integrations. Your expertise in programming, machine learning, and performance optimization will be essential in delivering high-quality applications. This position offers a dynamic environment where you can stay at the forefront of AI and frontend technologies, making a significant impact on product development and user engagement.

Formación

• Bachelor’s degree in Computer Science or related field is required.
• Proficiency in relevant programming languages and AI/ML concepts.

Responsabilidades

• Develop user-friendly web applications utilizing AI technologies.
• Collaborate with UX/UI designers to create intuitive interfaces.

Conocimientos

Programming Languages

AI / ML Experience

Responsive Design

Problem-Solving Skills

Communication

Educación

Bachelor’s degree in Computer Science

Bachelor’s degree in Software Engineering

Herramientas

React

Angular

Vue

TypeScript

Git

Jest

Cypress

Descripción del empleo

As a Frontend AI Engineer, you will be responsible for developing seamless and intuitive user interfaces that integrate artificial intelligence technologies. You will work closely with product managers, designers, and backend engineers to bring AI features to life, ensuring a responsive and engaging experience for our users.

Key Responsibilities :

1. Develop Interactive Interfaces :
   • Design and implement user-friendly, responsive web applications that utilize AI technologies to enhance user experience.
   • Work closely with data scientists and backend engineers to integrate AI models into frontend applications, ensuring seamless functionality.
2. User Experience (UX) Design :
   • Collaborate with UX / UI designers to create intuitive interfaces that leverage AI features effectively, focusing on usability and aesthetic appeal.
3. Performance Optimization :
   • Monitor and optimize the performance of frontend applications, ensuring fast load times and smooth interactions, especially when processing AI-related tasks.
   • Implement data visualization tools and libraries to present AI insights and outputs in an understandable and engaging format.
4. Testing and Quality Assurance :
   • Conduct thorough testing for functionality, performance, and security of the frontend applications, including usability testing for AI-powered features.
5. Documentation :
   • Maintain clear and comprehensive documentation for codebases and AI model integrations to support team collaboration and future development.
6. Stay Up to Date :
   • Keep abreast of the latest trends and advancements in AI, machine learning, and frontend technologies to recommend and implement improvements.

Skills and Qualifications :

1. Educational Background : Bachelor’s degree in Computer Science, Software Engineering, or a related field;
2. Programming Languages : Proficiency in relevant programming languages;
3. AI / ML Experience :
   • Familiarity with machine learning concepts and libraries (e.G., TensorFlow.Js, PyTorch) is essential for integrating AI functionality.
   • Knowledge of APIs and experience with data formats like JSON or XML to retrieve and transmit data effectively.
4. Responsive Design : Strong understanding of responsive web design principles and techniques.
5. Problem-Solving Skills : Strong analytical and problem-solving abilities, especially in troubleshooting frontend issues related to AI implementations.
6. Version Control : Experience with version control systems such as Git.
7. Communication : Excellent communication and teamwork skills to work effectively with cross-functional teams.

Tools & Technologies

1. Frontend : Proficiency in React / Angular / Vue, TypeScript, and state management.
2. AI / ML : Experience with client-side ML libraries and API integration (e.G., REST, GraphQL).
3. Performance : Knowledge of Web Workers, caching, and model optimization.
4. Testing : Familiarity with Jest / Cypress for AI feature validation.