Senior Multimodal AI Engineer: Vision, Audio & Speech

Meta; Salt Lake City (UT); Sur place; USD 154 000 - 217 000; Plein temps

Résumé du poste

Meta is seeking a talented engineer for Applied AI's Multimedia & Multimodality team in Salt Lake City. You will own data production and measurement across image, video, audio, and speech modalities, building pipelines and evaluation tools.

You will design agentic workflows, scalable data pipelines, training efficiency improvements, and reproducibility measures while mentoring teammates. Translate research ideas into practical systems that raise quality and impact.

Qualifications

• Bachelor's degree in CS/CE or equivalent practical experience.
• 6+ years of programming in a relevant language or 3+ years with a PhD.
• 3+ years building ML systems in production or research.
• Strong Python and PyTorch.
• Experience with speech, audio, or music ML (ASR, TTS, codecs, etc.).
• Experience with large-scale data pipelines and distributed training.
• Track record translating research ideas into working systems.

Responsabilités

• Design and build agentic workflows and pipelines with human-in-the-loop designs.
• Design and own data pipelines at scale: ingestion, filtering, labeling, and captioning.
• Build evaluation infrastructure: metrics, listening tests, and correlation analysis.
• Improve training efficiency: distributed training, GPU utilization, retraining.
• Reproduce and extend state-of-the-art research by implementing papers.
• Mentor engineers and contribute to hiring and onboarding.
• Build and train generative models for speech, sound, and music.

Connaissances

Python

PyTorch

Distributed training

ML systems

Speech/Audio ML

Data pipelines

Formation

Bachelor's degree in CS/CE or equivalent

PhD (optional)

Description du poste

Meta is seeking a talented engineer for Applied AI's Multimedia & Multimodality team in Salt Lake City. You will own data production and measurement across image, video, audio, and speech modalities, building pipelines and evaluation tools.

You will design agentic workflows, scalable data pipelines, training efficiency improvements, and reproducibility measures while mentoring teammates. Translate research ideas into practical systems that raise quality and impact.