Senior Multimodal AI Engineer — Multimedia & Audio

Meta; City of Albany (NY); On-site; USD 184,000 - 257,000; Full time

Job summary

Meta is seeking a Senior Engineer in Applied AI to lead end-to-end multimodal projects across image, video, audio, and speech. You will decide data to produce, define measurements, and drive pipelines from conception to production, setting standards for the team and collaborating with research, engineering, and product partners.

You will build agentic workflows, design data pipelines, and develop evaluation infrastructure to align model outputs with measured quality, while mentoring teammates

Qualifications

• Bachelor's degree in CS, CE or equivalent practical experience.
• 8+ years programming OR 4+ years with a PhD.
• 3+ years building ML systems in production or research.
• Strong Python and PyTorch.
• Experience with speech, audio, or music ML.
• Experience with large-scale data pipelines and distributed training.
• Track record translating research ideas into working, measurable systems.

Responsibilities

• Set technical direction for a modality or capability area across the team.
• Design and build agentic workflows and pipelines with human-in-the-loop designs.
• Own data pipelines: ingestion, filtering, pseudo-labeling and captioning; provenance tracking.
• Build evaluation infrastructure: objective metrics and human listening-test pipelines.
• Improve training efficiency and reliability: distributed training and experiment management.
• Reproduce and extend state-of-the-art research by implementing methods from papers.

Skills

Python

PyTorch

Distributed training

ML systems

Speech/audio/music ML

Education

Bachelor's degree in Computer Science / Computer Engineering or equivalent practical experience

Tools

PyTorch

Job description

Meta is seeking a Senior Engineer in Applied AI to lead end-to-end multimodal projects across image, video, audio, and speech. You will decide data to produce, define measurements, and drive pipelines from conception to production, setting standards for the team and collaborating with research, engineering, and product partners.

You will build agentic workflows, design data pipelines, and develop evaluation infrastructure to align model outputs with measured quality, while mentoring teammates