Staff Machine Learning Engineer, Siri Attention and Invocation

Apple Inc.; Zürich; Vor Ort; CHF 180.000 - 280.000; Vollzeit

Zusammenfassung

Apple is seeking a Staff Machine Learning Engineer to lead the development of audio and video generation capabilities for Siri Runtime Systems and Interaction. You will shape the technical vision for expressive synthetic speech and visuals, mentor engineers, and drive multimodal generative experiences across products.

You will design end-to-end systems for synthetic audio and video, lead projects from research to production, set evaluation standards, and collaborate across research, product,

Qualifikationen

• Master’s or PhD in CS/EE/ML or equivalent practical experience.
• Hands-on experience with generative audio/video architectures (diffusion, autoregressive, GANs, VAEs).
• Ability to lead complex projects from research to production under real-world constraints (quality, latency, compute).
• Experience evaluating generative model outputs using objective and perceptual metrics.

Aufgaben

• Design end-to-end systems for generating synthetic audio (speech, acoustics, sound) and/or video for agents interaction.
• Lead complex generative AI projects from research prototype through large-scale production deployment.
• Establish best practices for model evaluation, perceptual quality assessment, and monitoring of generative outputs.
• Drive architecture for multimodal (audio/video) generation with latency and scalability considerations.
• Identify opportunities where advances in generative modeling improve agent experiences.
• Collaborate with research, product, design, and infrastructure teams to translate techniques into shipped features.
• Mentor engineers and raise the ML engineering bar across the team.
• Stay current with diffusion, autoregressive, and end-to-end architectures and their applicability.

Kenntnisse

Generative modeling

Leadership

Python

PyTorch

TensorFlow

Research to production

Ausbildung

Master's or PhD in CS/EE/ML

Tools

PyTorch

TensorFlow

Distributed training

Jobbeschreibung

Staff Machine Learning Engineer, Siri Runtime Systems and Interaction

As 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.

Description

We 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.

Responsibilities

• Design and implement end-to-end systems for generating synthetic audio (speech, acoustics, sound) and/or video for agents interaction
• Lead complex generative AI projects from research prototype through large-scale production deployment
• Establish best practices for model evaluation, perceptual quality assessment, and monitoring of generative outputs
• Drive technical decisions and architecture for multimodal (audio/video) generation systems, balancing quality, latency, and scalability
• Identify high-impact opportunities where advances in generative modeling can meaningfully improve agents experiences
• Collaborate closely with research, product, design, and infrastructure teams to translate cutting-edge techniques into shipped features
• Mentor and provide technical guidance to engineers across the team, raising the bar for ML engineering practices
• Stay current with emerging techniques in generative modeling (e.g., diffusion, autoregressive, end-to-end architectures) and evaluate their applicability to our systems

Minimum Qualifications

• Master’s or PhD in Computer Science, Electrical Engineering, Machine Learning, or a related field, or equivalent practical experience
• Deep hands-on experience with generative audio and/or video architectures (e.g., diffusion models, autoregressive models, GANs, VAEs, end-to-end neural synthesis)
• Demonstrated ability to lead complex, ambiguous projects from research through production, and to make sound technical tradeoffs under real-world constraints (quality, latency, compute)
• Experience evaluating generative model outputs, including both objective metrics and perceptual/subjective quality assessment

Preferred Qualifications

• Proven experience building and shipping machine learning systems in production, with significant focus on generative modeling
• Excellent collaboration and communication skills, with a track record of working across research, engineering, and product teams
• Strong software engineering skills, with experience designing scalable ML systems and pipelines (e.g., Python, PyTorch/TensorFlow, distributed training infrastructure)
• Experience with speech synthesis (TTS), voice conversion, audio acoustics/background modeling, or conversational AI systems
• Experience with generative video/animation techniques (e.g., facial animation, lip-sync, avatar rendering, video diffusion)
• Publications in generative modeling, speech, audio, or computer vision at top-tier venues (e.g., NeurIPS, ICML, ICASSP, CVPR, Interspeech)
• Experience deploying real-time or low-latency generative models at scale
• Familiarity with multimodal modeling (joint audio-visual generation, cross-modal conditioning)
• Prior experience mentoring engineers or leading technical direction for a team

At 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.

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