Senior Multimodal AI Engineer: Audio, Video & Speech

Meta; Honolulu (HI); On-site; USD 184,000 - 257,000; Full time

Job summary

Meta’s Applied AI organization seeks a senior engineer to lead end-to-end multimodal initiatives across image, video, audio, and speech. You will decide what data to produce, define how it is measured, and drive it from inquiry to scalable pipelines and measurable outcomes for the organization.

You will own data and evaluation pipelines, shape project scope, mentor engineers, and help raise the bar on quality and responsible AI practices.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, or equivalent practical experience.
• 8+ years of programming experience in a relevant language OR 4+ years experience with a 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

• Set technical direction for a modality or capability area.
• Determining where the team invests, what success means, and the tradeoffs behind both.
• Drive that direction across partner teams, not just inside your own.
• 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

Strategic thinking

Cross-functional collaboration

Mentoring engineers

Hiring and onboarding

Experimentation/ablations

AI systems thinking

Education

Bachelor's degree in Computer Science/Engineering or equivalent

8+ years programming OR 4+ years with PhD

Tools

Python

PyTorch

Distributed training

Data pipelines

Evaluation infrastructure

Job description

Meta’s Applied AI organization seeks a senior engineer to lead end-to-end multimodal initiatives across image, video, audio, and speech. You will decide what data to produce, define how it is measured, and drive it from inquiry to scalable pipelines and measurable outcomes for the organization.

You will own data and evaluation pipelines, shape project scope, mentor engineers, and help raise the bar on quality and responsible AI practices.