7 months ago

Member of Technical Staff - Multi-Modal, Audio

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Join a fast-moving Audio team developing frontier speech-language models with on-device, real-time constraints. You will own data pipelines, evaluation systems, and customer deployments, contributing production code to core audio repos while collaborating with infrastructure and research teams. Expect high ownership, cross-functional work streams, and rapid iteration on production ML systems in a small, elite team.

Location: San Francisco, Boston, Cambridge

Workplace: Hybrid

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•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
•Support experimentation under real hardware constraints, shifting between customer work and core development as priorities evolve

Pay and Benefits

Equity and Bonus:Equity

Perks:Health Insurance401kEquityPaid Leave

Key Requirements

•Strong programming fundamentals with demonstrated ability to write clean, maintainable, production-grade code
•Experience building and shipping production ML systems beyond model training (data pipelines, evals, serving infrastructure)
•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
•Experience designing for on-device, low-latency, memory-limited environments

Experience:AIAudioMultimodalOn-device computing

Skills:CommunicationCollaborationProblem-solvingOwnershipTeamwork

Languages:English

Tech Stack:PythonPyTorchDeepSpeedFSDPOn-deviceMultimodal

Company Brief

Liquid AI

Builds AI infrastructure and tooling to enable real-time, distributed machine learning and orchestration across edge and cloud environments, simplifying deployment and management of intelligent applications.

Industry: AI & Machine Learning

Website

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Liquid AI

7 months ago

Member of Technical Staff - Multi-Modal, Audio

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: San Francisco, Boston, Cambridge

Workplace: Hybrid

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•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
•Support experimentation under real hardware constraints, shifting between customer work and core development as priorities evolve

Pay and Benefits

Equity and Bonus:Equity

Perks:Health Insurance401kEquityPaid Leave

Key Requirements

•Strong programming fundamentals with demonstrated ability to write clean, maintainable, production-grade code
•Experience building and shipping production ML systems beyond model training (data pipelines, evals, serving infrastructure)
•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
•Experience designing for on-device, low-latency, memory-limited environments

Experience:AIAudioMultimodalOn-device computing

Skills:CommunicationCollaborationProblem-solvingOwnershipTeamwork

Languages:English

Tech Stack:PythonPyTorchDeepSpeedFSDPOn-deviceMultimodal

Company Brief

Liquid AI

Industry: AI & Machine Learning

Website