Senior Multimodal AI Engineer: Media Pipelines & Evaluation

Meta; Cheyenne (WY); On-site; USD 184,000 - 257,000; Full time

Benefits offered by this job

Bonus

Equity

Benefits

Job summary

Meta's Applied AI organization, part of the Multimedia & MultiModality team, seeks a senior engineer to lead multimodal data pipelines, evaluation, and model workflows across image, video, audio, and speech. You will own data decisions, measurement strategies, and end-to-end pipelines that drive measurable outcomes for research and engineering partners.

You will mentor engineers, set engineering standards, and collaborate across teams to convert open questions into scalable, robust systems.

Qualifications

• Bachelor's degree in CS 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 systems.

Responsibilities

• Set technical direction for a modality or capability area.
• Drive direction across partner teams.
• Design and build agentic workflows and pipelines with human-in-the-loop designs.
• Own data pipelines at scale: ingestion, labeling, captioning, provenance.
• Build evaluation infrastructure and correlate metrics with human tests.
• Improve training efficiency and reliability via distributed training.
• Reproduce and extend state-of-the-art research in codebases.
• Mentor engineers and contribute to hiring and onboarding.
• Build and train generative/representation models for speech, sound, and music.

Skills

Python

PyTorch

ML systems

Distributed training

Multimodal AI

Leadership

Education

Bachelor's in CS

PhD (preferred)

Tools

GPU clusters

Job description

Meta's Applied AI organization, part of the Multimedia & MultiModality team, seeks a senior engineer to lead multimodal data pipelines, evaluation, and model workflows across image, video, audio, and speech. You will own data decisions, measurement strategies, and end-to-end pipelines that drive measurable outcomes for research and engineering partners.

You will mentor engineers, set engineering standards, and collaborate across teams to convert open questions into scalable, robust systems.