Principal AI Engineer, Media Pipelines

Liquid StudiosAI media processing

Remote (United States Only)Full-TimePrincipal

Salary$175K - $200K; $175K – $200K • Offers Equity

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Job Details

Typically 10+ years building software.
Experience as the technical owner of a production system with real users, uptime commitments, and cost constraints.
Experience shipping generative AI systems, such as LLM or multimodal systems, agentic workflows, multi-step pipelines, or RAG, to production.
Experience handling production AI evaluations, retries, failure modes, and cost.
Deep experience in Python and/or TypeScript.
Experience with at least one major cloud platform.
Strong grounding in job orchestration, queues, storage, and databases for large, long-running, failure-prone workloads.
Experience setting technical direction for systems other engineers build on through design docs, reviews, and mentoring.
Nice to have: media processing experience with FFmpeg, codecs and containers, transcoding, loudness normalization, or caption and subtitle formats.
Nice to have: speech and audio ML, video understanding, self-hosting open-source models on GPUs, or retrieval and vector search over large content catalogs.

Set the technical direction for media ingestion, transformation, quality control, and delivery, including orchestration, data models, and service boundaries.
Choose what to build, buy, or fine-tune across LLMs, speech recognition, text-to-speech, translation, and video models.
Run structured model bake-offs and design the pipeline so providers can be swapped without a rewrite.
Manage processing cost, latency, and throughput through batching, caching, routing, and graceful degradation.
Build evaluations and automated quality gates for dub naturalness and sync, translation accuracy, clip selection, and brand compliance.
Define SLOs, observability, incident response, and data handling for client catalogs.
Work with leadership on voice-cloning consent, likeness, content rights, and AI disclosure, and incorporate requirements into the pipeline.
Set engineering standards, mentor engineers through pairing and review, and deliver high-priority roadmap features from prototype to production.

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