Multimodal AI Engineer: Build Media Pipelines & Evaluation

Meta; Olympia (WA); On-site; USD 154,000 - 217,000; Full time

Job summary

Meta is seeking a Software Engineer in Multimedia & Multimodal AI to advance multimodal data production, evaluation, and model development across image, video, audio, and speech modalities. You will own data pipelines, metrics, and architecture decisions that impact model quality and research direction.

You will work across ingestion, labeling, evaluation, and training efficiency, mentoring teammates while helping set engineering standards for scalable, responsible AI practices.

Qualifications

• 3+ years building ML systems in production or research settings.
• Strong Python and PyTorch.
• Demonstrated experience with speech, audio, or music ML (ASR, TTS, codecs, music IR, etc).
• Experience with large-scale data pipelines and distributed training.
• Track record of translating research ideas into working, measurable systems.

Responsibilities

• Design and build agentic workflows and pipelines, including human-in-the-loop designs, to automate data production and scale output.
• Design and own data pipelines at scale: ingestion, filtering, pseudo-labeling and captioning with attribute classifiers, and provenance tracking for audio corpora.
• Build evaluation infrastructure: objective metrics, human listening-test pipelines, and correlation analysis.
• Improve training efficiency and reliability — distributed training, GPU utilization, codec and tokenizer retraining, experiment management.
• Reproduce and extend state-of-the-art research: implement new methods from papers into codebases and run ablations.
• Mentor engineers on the team, contribute to hiring and onboarding, and raise the bar on evaluation and quality practice.
• Build and train generative and representation models for speech, sound, and music.

Skills

3+ years ML systems

Python

PyTorch

Speech/audio/music ML

Large-scale data pipelines

Job description

Meta is seeking a Software Engineer in Multimedia & Multimodal AI to advance multimodal data production, evaluation, and model development across image, video, audio, and speech modalities. You will own data pipelines, metrics, and architecture decisions that impact model quality and research direction.

You will work across ingestion, labeling, evaluation, and training efficiency, mentoring teammates while helping set engineering standards for scalable, responsible AI practices.