Staff ML Engineer — Multimodal Generative Audio/Video

Lex; Zürich; Vor Ort; CHF 140.000 - 210.000; Vollzeit

Zusammenfassung

Apple seeks a Staff Machine Learning Engineer in Zürich to lead the development of audio and video generation capabilities across multimodal agents. You will define the technical vision for expressive synthetic speech and visuals and mentor engineers across the team.

You will collaborate with research, product, design and infrastructure to translate cutting-edge techniques into shipped features, evaluate outputs, and balance quality with latency and compute to scale with real-world demand.

Qualifikationen

• Master’s or PhD in CS/EE/ML or equivalent experience.
• Hands-on experience with generative audio and/or video models (diffusion, autoregressive, GANs/VAEs).
• Proven ability to lead complex projects from research to production with tradeoffs on quality, latency, and compute.
• Experience evaluating generative outputs using objective and perceptual metrics.

Aufgaben

• Design and implement end-to-end systems for synthetic audio and/or video generation.
• Lead research-to-production efforts on multimodal generative projects.
• Establish evaluation protocols and monitor quality and latency of outputs.
• Guide architecture decisions for scalable, low-latency generation systems.
• Mentor engineers and raise ML engineering standards across the team.
• Collaborate with research, product, design, and infra teams to ship features.
• Stay current with diffusion, autoregressive, and end-to-end generative techniques.

Kenntnisse

Generative ML

Leadership

Research-to-production

System design

Python

Ausbildung

Master’s or PhD in Computer Science/EE/ML

Tools

PyTorch

TensorFlow

Distributed training

Diffusion models

GANs/VAEs

End-to-end synthesis

Jobbeschreibung

Apple seeks a Staff Machine Learning Engineer in Zürich to lead the development of audio and video generation capabilities across multimodal agents. You will define the technical vision for expressive synthetic speech and visuals and mentor engineers across the team.

You will collaborate with research, product, design and infrastructure to translate cutting-edge techniques into shipped features, evaluate outputs, and balance quality with latency and compute to scale with real-world demand.