Senior Multimodal AI Engineer — End-to-End Pipelines

Meta; Montpelier (VT); Remote; USD 184,000 - 257,000; Full time

Job summary

Meta’s Applied AI (AAI) organization is hiring a senior engineer to lead multimodal data, pipelines and evaluation end-to-end. You will own a modality or capability area, decide what data to produce and how to measure it, and carry it from open questions to automated workflows.

You will work across image, video, audio and speech, building scalable data and evaluation infrastructure, mentoring engineers, and advancing research into production.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, or equivalent practical experience.
• 8+ years of programming in a relevant language OR 4+ years 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, codecs, MIR, self-supervised audio representations, or audio generation).
• 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.
• Determine 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.
• 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 analyses.
• Improve training efficiency and reliability — distributed training, GPU utilization, and tokenizer retraining.
• Reproduce and extend state-of-the-art research by implementing methods from papers.
• Mentor engineers on the team, contribute to hiring and onboarding, raise the bar on evaluation and quality.
• Build and train generative and representation models for speech, sound, and music.

Skills

Python

PyTorch

Multimodal ML

Speech / Audio ML

Data Pipelines

Distributed Training

Research to Production

Education

Bachelor's degree in Computer Science / related field

PhD with 4+ years experience

Job description

Meta’s Applied AI (AAI) organization is hiring a senior engineer to lead multimodal data, pipelines and evaluation end-to-end. You will own a modality or capability area, decide what data to produce and how to measure it, and carry it from open questions to automated workflows.

You will work across image, video, audio and speech, building scalable data and evaluation infrastructure, mentoring engineers, and advancing research into production.