Camera Software- Sr. Machine Learning Research Engineer

Apple Apple · Big Tech · San Francisco Bay Area · Machine Learning and AI

Research Engineer role focused on developing and fine-tuning generative models for Apple's camera software, specifically for computational photography applications on iPhone and iPad. The role involves designing model architectures, training strategies, building data pipelines, and developing evaluation frameworks, with a strong emphasis on vision and image generation.

What you'd actually do

  1. Design novel generative model architectures and training strategies for vision and computational photography applications.
  2. Fine-tune and adapt pre-trained models for specific use cases and domains.
  3. Build scalable and robust data pipelines for large-scale image and video datasets.
  4. Develop comprehensive evaluation frameworks including implementing quantitative metrics and qualitative analysis methodologies, conducting ablation studies and hyper-parameter optimization, for model performance assessment.
  5. Conduct deep technical analysis and identify research directions.

Skills

Required

  • PhD or MS + 3 years industry experience
  • Solid foundation in image processing, computer vision and deep learning fundamentals
  • Academic or project experience with image/video generation models
  • Deep technical analysis
  • Research directions identification
  • Code reviews
  • Technical discussions
  • Knowledge sharing sessions
  • Documentation
  • Presentations
  • Latest research in generative AI, computer vision and computational photography

Nice to have

  • Minimum PhD + 2 years or MS + 5 years industry experience
  • Expertise in image processing, computer vision and deep learning
  • Strong experience with deep learning frameworks (e.g. PyTorch) and modern ML toolchains
  • Proven experience with training and developing generative models
  • Hands-on with multi-GPU/multi-node/distributed training and large-scale experimentation
  • Curiosity-driven with a track-record of identifying and solving complex technical problems
  • Excellent communication skills
  • Ability to bridge gap between technical depth and product impact
  • Collaborative mindset
  • Openness to feedback and continuous learning
  • Publications at major conferences (CVPR, ICCV, NeurIPS, ICML) or open-source contributions

What the JD emphasized

  • PhD or MS + 3 years industry experience
  • Solid foundation in image processing, computer vision and deep learning fundamentals
  • Academic or project experience with image/video generation models
  • Proven experience with training and developing generative models
  • Hands-on with multi-GPU/multi-node/distributed training and large-scale experimentation

Other signals

  • develops innovative algorithms
  • work hands-on with diffusion models, transformers and next-gen generative techniques
  • collaborating closely with product, design and research teams
  • inventing and developing new imaging algorithms