At Apple, new ideas have a way of becoming phenomenal products, services, and customer experiences very quickly! The Productivity Apps team, the team behind apps like Notes, Freeform, and iWork needs your help shaping the next generation of productivity tools by working on pioneering technologies to surprise and delight our users. As a Machine Learning Engineer, you will be working alongside our world-class creatives, designers, and engineers to help innovate in the productivity space in ways that only Apple can. This is a highly visible, highly impactful opportunity!
Join our research-oriented engineering team, and you'll build state-of-the-art generative models and applications, partner with cross-functional teams, and deliver end-to-end features to power the next-generation creative tools. The ideal candidate should have deep experience in generative modeling, care about long-term sustainable software development, and can drive features from concept all the way to delivery. This position requires a self-motivated individual with excellent interpersonal skills to effectively collaborate with all levels of the organization.
MS + 2 years of industry experience or PhD in Computer Science, Computer Vision, Machine Learning, or related field with publications in generative models\nHands-on experience training generative models such as diffusion models, GANs, VAEs, or autoregressive image models. Strong programming skills in PyTorch or JAX.
Experience with compositional or layout-conditioned image generation, or image decomposition/editing\nExperience deploying models to memory or compute constrained environments. Experience with large-scale model training and parallelization.\nTrack record of publications in top-tier machine learning or computer vision conferences (e.g., CVPR, ICCV, ECCV, NeurIPS/ICML, SIGGRAPH, CHI).
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: 90733111
- Position Id: a677144dad073257ec0b3dc9b81ac7c9
- Posted 3 days ago
Never miss an opportunity! Create an alert based on the job you applied for.