Staff Machine Learning Engineer, Siri Runtime Systems and Interaction

ph3Summary /h3 pAs part of Siri Attention and Invocation, we collaborate to deliver the next revolution in human‑computer interaction, to inspire and create groundbreaking technology for large‑scale systems spanning speech, vision, and generative AI to overcome real‑world challenges through innovation and user‑centered design that improves the daily experience of millions of our customers. /p h3Description /h3 pWe are seeking an exceptional Staff Machine Learning Engineer to lead the development of audio and video generation capabilities. In this role, you will drive the technical vision for generating realistic, expressive synthetic speech and visual representations, mentor senior and junior engineers, and shape the roadmap for multimodal generative experiences across our products. /p h3Responsibilities /h3 ul liDesign and implement end‑to‑end systems for generating synthetic audio (speech, acoustics, sound) and/or video for agents interaction /li liLead complex generative AI projects from research prototype through large‑scale production deployment /li liEstablish best practices for model evaluation, perceptual quality assessment, and monitoring of generative outputs /li liDrive technical decisions and architecture for multimodal (audio/video) generation systems, balancing quality, latency, and scalability /li liIdentify high‑impact opportunities where advances in generative modeling can meaningfully improve agents experiences /li liCollaborate closely with research, product, design, and infrastructure teams to translate cutting‑edge techniques into shipped features /li liMentor and provide technical guidance to engineers across the team, raising the bar for ML engineering practices /li liStay current with emerging techniques in generative modeling (e.g., diffusion, autoregressive, end‑to‑end architectures) and evaluate their applicability to our systems /li /ul h3Minimum Qualifications /h3 ul liMaster's or PhD in Computer Science, Electrical Engineering, Machine Learning, or a related field, or equivalent practical experience /li liDeep hands‑on experience with generative audio and/or video architectures (e.g., diffusion models, autoregressive models, GANs, VAEs, end‑to‑end neural synthesis) /li liDemonstrated ability to lead complex, ambiguous projects from research through production, and to make sound technical tradeoffs under real‑world constraints (quality, latency, compute) /li liExperience evaluating generative model outputs, including both objective metrics and perceptual/subjective quality assessment /li /ul h3Preferred Qualifications /h3 ul liProven experience building and shipping machine learning systems in production, with significant focus on generative modeling /li liExcellent collaboration and communication skills, with a track record of working across research, engineering, and product teams /li liStrong software engineering skills, with experience designing scalable ML systems and pipelines (e.g., Python, PyTorch/TensorFlow, distributed training infrastructure) /li liExperience with speech synthesis (TTS), voice conversion, audio acoustics/background modeling, or conversational AI systems /li liExperience with generative video/animation techniques (e.g., facial animation, lip‑sync, avatar rendering, video diffusion) /li liPublications in generative modeling, speech, audio, or computer vision at top‑tier venues (e.g., NeurIPS, ICML, ICASSP, CVPR, Interspeech) /li liExperience deploying real‑time or low‑latency generative models at scale /li liFamiliarity with multimodal modeling (joint audio‑visual generation, cross‑modal conditioning) /li liPrior experience mentoring engineers or leading technical direction for a team /li /ul pAt Apple, we're not all the same. And that's our greatest strength. We draw on the differences in who we are, what we've experienced, and how we think. Because to create products that serve everyone, we believe in including everyone. Therefore, we are committed to treating all applicants fairly and equally. We will work with applicants to make any reasonable accommodations. /p pAt Apple, we believe accessibility is a fundamental human right. You'll find that idea reflected in everything here - in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong. /p pLearn about accessibility in Apple's workplace /p pRole Number: /p /p #J-18808-Ljbffr