Multimodal AI Engineer — Media Pipelines & Evaluation

Meta; United States; On-site; USD 154,000 - 217,000; Full time

Benefits offered by this job

Bonus

Equity

Benefits

Job summary

Meta is seeking a Software Engineer for Multimedia & Multimodal AI to own data and evaluation pipelines across image, video, audio, and speech modalities. You will design end-to-end data production, annotations, and evaluations, collaborating with research and engineering partners to push multimodal capabilities beyond text.

You will mentor teammates, improve training efficiency, and contribute to building scalable, high-quality AI systems for multimedia tasks.

Qualifications

• Bachelor's degree in CS/engineering or equivalent practical experience.
• 6+ years programming or 3+ years with PhD.
• 3+ years building ML systems in production or research settings.
• Strong Python and PyTorch.
• Experience with speech, audio or music ML and large-scale data pipelines.
• Experience translating research ideas into working systems.

Responsibilities

• Design and build agentic workflows and data production pipelines.
• Own data pipelines for ingestion, filtering, labeling, and provenance tracking for audio corpora.
• Build evaluation infrastructure with objective metrics and listening-test pipelines.
• Improve training efficiency and reliability via distributed training and resource management.
• Reproduce and extend state-of-the-art research by implementing methods from papers.
• Mentor engineers, contribute to hiring and onboarding, raise quality standards.
• Develop generative and representation models for speech, audio, and music.

Skills

Python

PyTorch

ML Systems

Distributed Training

Speech Audio Music ML

Data Pipelines

Research to Production

Education

Bachelor's degree in CS/Engineering

PhD (optional)

Job description

Meta is seeking a Software Engineer for Multimedia & Multimodal AI to own data and evaluation pipelines across image, video, audio, and speech modalities. You will design end-to-end data production, annotations, and evaluations, collaborating with research and engineering partners to push multimodal capabilities beyond text.

You will mentor teammates, improve training efficiency, and contribute to building scalable, high-quality AI systems for multimedia tasks.