Computer Vision Backend Engineer

Key Skills

AWS, Azure, C++, Computer Vision (CV), Continuous Integration & Continuous Delivery - CI/CD, Docker, Google Cloud Platform (GCP), GraphQL, Keras software library, Kubernetes-K8s, Machine learning techniques, Optimization, Python Programming, PyTorch, TensorFlow

Job Description

As a member of our dynamic and fast-paced group, you'll play a key role in crafting and bringing to life innovative solutions that delight millions of customers across the globe. You will design and implement large-scale CV/ML solutions integrating the latest state of the art research in our global products to enhance our customer experience.

While collaborating with partner teams across Apple, you'll contribute by sharing your experience, delivering architectural proposals that account for international market needs, and maintaining an ethos of continual learning from your counterparts. This position is at the intersection of Computer Vision, Machine Learning and Software Engineering.

The ideal candidate will have expertise with computer vision and deep learning models, machine learning lifecycle management, data generation methods, model training & validation coupled with strong fundamentals and passion in software engineering and system architecture. Join us navigate the forefront of the computer vision evolution!

Minimum Qualifications

• Experience in Machine Learning (ML), with a particular emphasis on Computer Vision (CV)
• Comprehensive knowledge and hands-on experience with fine-tuning approaches and training models
• Proven ability to comprehend, interpret, and apply cutting-edge research into consumer-oriented products
• Previous experience in computer vision projects, particularly those focusing on backend integration
• Experience with TensorFlow, PyTorch or Keras
• Proficiency in Python is essential, especially with libraries such as NumPy, OpenCV, and scikit-image
• Experience with databases (SQL and NoSQL) for managing datasets.
• Understanding of APIs (REST, GraphQL) for connecting computer vision models with frontend or other backend services
• Knowledge of cloud services (AWS, Azure, Google Cloud) for deploying and managing models
• Experience with Docker and Kubernetes for containerization and deployment
• Understanding of software development best practices, version control (Git), and CI/CD pipelines.

Preferred Qualifications

• Experience adapting pre-trained LLMs for downstream tasks
• Knowledge of C++ is advantageous for performance optimization and working with low-level vision algorithms.
• Familiarity with research papers, implementing state-of-the-art methods, and adapting them to practical applications
• Experience working in cross-functional teams
• Experience with deploying models in production environments