Job Summary

At Airbus, we are harnessing the power of artificial intelligence to enhance efficiency and quality across our value chain. Our team is composed of technologists and business leaders dedicated to innovation and excellence. We are seeking a versatile, agile, and curious Full Stack Developer with Machine Learning knowledge to join our high-impact Computer Vision Team.

In this role, you will work at the intersection of web development and applied AI. You will be instrumental in building end-to-end Computer Vision applications ranging from designing responsive user interfaces and robust backend APIs to integrating and optimizing machine learning models.

We are looking for a fast learner who thrives in a dynamic environment and is eager to switch context between frontend, backend, or ML model pipelines based on project needs.

Qualification & Experience

Education: Graduate / Post Graduate degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, or a related field. Experience: 0 to 3 years of hands-on experience in software development with exposure to machine learning workflows.

Key Responsibilities

- Full-Stack Application Development: Design, build, and maintain scalable web applications (frontend UI and backend services) to interface with Computer Vision models.
- Computer Vision & ML Integration: Assist in training, fine-tuning, evaluating, and deploying CV algorithms (object detection, image classification, segmentation, tracking) into production workflows.
- Adaptive Task Execution: Seamlessly shift focus across frontend features, backend API design, or data pipeline/model optimization depending on sprint priorities.
- Data Pipeline & Preprocessing: Help prepare, annotate,



and manage image/video datasets required for model training and testing.
- Cloud & Infrastructure: Leverage cloud platforms (AWS/GCP) to host services, store unstructured visual data, and run inference pipelines.
- Collaboration: Work closely with senior ML engineers, product managers, and UI/UX designers to translate requirements into functional, high-performing features.
- Continuous Improvement: Keep up with the latest tech trends in web frameworks, cloud services, and computer vision techniques to keep our stack modern.

Technical Essentials

- Backend Development: Proficiency in Python (FastAPI, Flask, or Django) and building RESTful APIs.
- Frontend Development: Experience with contemporary JavaScript frameworks (React, Vue.js, or Angular) and responsive web design (HTML5/CSS3).
- Computer Vision & ML: Solid understanding of basic ML concepts and hands-on experience with tools like OpenCV, PyTorch, or TensorFlow (handling image/video data).
- Cloud Exposure: Basic working knowledge or certification in AWS (e.g., S3, EC2, Lambda) or GCP (e.g., Vertex AI, Cloud Run, GCS).
- Database Management: Basic proficiency in relational (PostgreSQL, MySQL) or NoSQL (MongoDB) databases.
- Version Control & Tooling: Familiarity with Git and containerization concepts (Docker).
- Testing & Quality Assurance:



Experience with automated testing frameworks (e.g., PyTest for backend, Jest/Cypress for frontend).

Soft Skills & Behavioral Attributes

- Fast Learning Curve: Demonstrated ability to quickly master new technologies, tools, and frameworks.
- Adaptability & Agility: Willingness to wear multiple hats writing frontend code one day and tweaking ML pipelines the next.
- Problem-Solving Mindset: Strong logical reasoning, analytical skills, and attention to detail.
- Communication: Clear written and verbal communication skills to articulate ideas effectively within a team environment.

Nice-to-Have / Added Advantages

- AWS or GCP Cloud certifications (e.g., AWS Certified Cloud Practitioner / Developer, GCP Associate Cloud Engineer).
- Prior experience with image annotation tools (e.g., CVAT, LabelImg).
- Exposure to MLOps tools (e.g., MLflow, DVC) or model deployment/quantization (ONNX, TensorRT).
- Active GitHub profile, Kaggle participation, or personal projects demonstrating end-to-end full-stack or computer vision implementations.
- AWS services like SageMaker and Step Functions.

Success Metrics

- Learning Velocity: Quick onboarding and rapid capability growth across new tech stacks and tools.
- Versatility & Speed: Ability to reliably deliver high-quality code across both frontend/backend tasks and ML model integration.
- Code Quality & Reliability: First-time-right approach to building maintainable, scalable, and bug

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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