Hiring: Member of Technical Staff - Multi-Modal, Audio Company: Liquid AI Location: San Francisco, CA Job Posted Time: 2026-09-11 10:30:51 Target Skills & Keywords : Data Pipeline, PyTorch, Systems Design About the job Experience: •Strong programming fundamentals with demonstrated ability to write clean, maintainable, production-grade code •Proficiency in PyTorch and familiarity with distributed training frameworks (DeepSpeed, FSDP, or similar) •Track record of collaborating effectively in shared codebases with high engineering standards Required Skills: •Builds first, theorizes later: You ship working systems, not just notebooks. Production-grade code is your default, not a stretch goal. •Owns outcomes end-to-end: From data pipelines to customer deployments, you take responsibility for the full stack without waiting for someone else to handle the hard parts. •Thrives under constraints: On-device, low-latency, memory-limited systems excite you. You see constraints as design parameters, not blockers. •Ramps quickly on new territory: Gaps in specific subdomains are fine if you close them fast. You seek out feedback and stay focused on what moves the needle. •Build and scale data pipelines for audio model training, including preprocessing, augmentation, and quality filtering at scale •Design, implement, and maintain evaluation systems that measure multimodal performance across internal and public benchmarks •Fine-tune and adapt audio models for customer-specific use cases, owning delivery from requirements through deployment •Contribute production code to the core audio repository, collaborating with infrastructure and research teams Qualifications: •Direct experience with audio/speech models (ASR, TTS, vocoders, diarization, or speech-to-speech systems) •Open-source contributions that demonstrate code quality and engineering judgment •What Success Looks Like (Year One) •Within 6 months, you independently deliver production-ready data pipelines or evaluation systems and own at least one customer workstream end-to-end •Your PRs to the core audio repo are accepted without heavy rework, demonstrating strong judgment in system design •By year end, you operate as a second pillar to the technical lead, unblocking parallel workstreams and raising overall team velocity Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!