Multimodal AI Systems Engineer: Multimedia Pipelines

Meta; Lansing (MI); On-site; USD 154,000 - 217,000; Full time

Benefits offered by this job

Bonus

Equity

Benefits

Job summary

Meta’s Applied AI (AAI) organization, within the Multimedia & Multimodal AI team, seeks a senior engineer to advance multimodal data production, evaluation, and model training now spanning image, video, audio, and speech modalities.

You will own data-driven measurement pipelines, set evaluation standards, and guide cross-functional partners while improving training efficiency and scaling research outputs. This role emphasizes leadership, collaboration, and hands-on model development.

Qualifications

• Bachelor's degree in Computer Science/Engineering or equivalent practical experience.
• 6+ years of programming experience in a relevant language or 3+ years with a PhD.
• 3+ years building ML systems in production or research settings.
• Strong Python and PyTorch experience.
• Demonstrated experience with speech, audio, or music ML (ASR, TTS, codecs, MR)
• 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 and expert-in-the-loop designs, to automate data production and scale output past what manual authoring supports.
• 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 (speaker/style similarity, codec and generator quality), 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 our codebases and run rigorous 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 — including text-, audio-, and video-conditioned generation, infilling, editing, and style transfer.

Skills

Agentic workflows

Data pipelines

Evaluation infrastructure

Training efficiency

State-of-the-art research

Mentorship

Generative modeling

Education

Bachelor's degree in CS/CE or equivalent

PhD (optional)

Tools

Python

PyTorch

Distributed training

Job description

Meta’s Applied AI (AAI) organization, within the Multimedia & Multimodal AI team, seeks a senior engineer to advance multimodal data production, evaluation, and model training now spanning image, video, audio, and speech modalities.

You will own data-driven measurement pipelines, set evaluation standards, and guide cross-functional partners while improving training efficiency and scaling research outputs. This role emphasizes leadership, collaboration, and hands-on model development.