Multimodal AI Engineer: Multimedia Pipelines & Evaluation

Meta; Helena (MT); On-site; USD 154,000 - 217,000; Full time

Job summary

Meta’s Applied AI organization seeks a seasoned software engineer to advance multimodal data pipelines and evaluation for speech, audio, and music. You will own data production, define metrics, and drive end-to-end pipelines across image, video, and audio modalities.

You will mentor engineers, contribute to hiring, reproduce state-of-the-art methods, and help raise quality and responsible AI practices while scaling systems in production.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• 6+ years of programming experience in a relevant language or 3+ years of experience + PhD
• 3+ years building ML systems in production or research settings
• strong Python and PyTorch
• Demonstrated experience with speech, audio, or music ML - ASR, TTS, audio codecs, music information retrieval, self-supervised audio representation learning, or audio generative modeling
• 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 the correlation analysis that ties the two together.
• 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

Python

PyTorch

ML systems

Multimodal ML

Distributed training

Data pipelines

Research-to-production

Education

Bachelor's degree in Computer Science/Engineering or equivalent

PhD (optional)

Job description

Meta’s Applied AI organization seeks a seasoned software engineer to advance multimodal data pipelines and evaluation for speech, audio, and music. You will own data production, define metrics, and drive end-to-end pipelines across image, video, and audio modalities.

You will mentor engineers, contribute to hiring, reproduce state-of-the-art methods, and help raise quality and responsible AI practices while scaling systems in production.