Senior Computer Vision and Machine Learning Engineer, Creativity Apps

As a Senior Computer Vision & Machine Learning Engineer, you will work alongside our world-class creatives, designers, and engineers to help innovate in the creative space in ways that only Apple can. This is a highly visible, highly impactful opportunity!

We are hiring a software engineer to work on a new initiative that will push the boundary of what's possible in the field of Generative AI. The ideal candidate will have deep knowledge in computational photography and multi-modal image editing. This position requires a self-motivated individual with excellent interpersonal skills to effectively collaborate with all levels of the organization., + MS or PhD in Computer Science, Machine Learning or related field, and 5+ years of significant industry experience delivering products using state-of-the-art computational photography and machine learning technologies.

• Extensive knowledge in theory and practice of machine learning and deep learning techniques, particularly diffusion models, variational auto-encoders and transformers.

• Experience delivering customer-facing products with computer vision, computational photography or generative AI features.

• Hands-on experience building, training, evaluating, and deploying diffusion, transformer and Generative Adversarial Network based models, or related methods.

• Experience contributing to large codebases while delivering high-quality software at scale.

• Strong programming skills in high-level languages like Python and one of the deep learning toolkits such as PyTorch, JAX, or TensorFlow.

• Ability to collaborate effectively across organizations and drive alignment in large cross-functional projects.

• Ability to concisely communicate with audiences of different backgrounds, from non-technical individuals to experts in the field.

• Committed to encouraging an open and inclusive work environment.

Preferred Qualifications

• Experience optimizing models and algorithms that run efficiently on resource-constrained platforms is a plus.

• Experience with flow matching and multi-modal conditioning for generative modeling is a plus.

• Familiarity with 3D reconstruction techniques from single or multiple images, particularly ML-based methods, is a plus.

• Knowledge of and keen interest in the art and science of photography and aesthetics.

• Publications at major conferences (CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR) is a plus.