Member of Technical Staff - Embedded ML Engineer (Audio/Omni)

Liquid AI
San Francisco
Workplace: HybridFull timeFunction: Data Science & Machine LearningExperience: 2+ yearsSkills: ["Communication","Client-ready communication","First-principles reasoning","Data wrangling","Ownership"]

Build and own an end-to-end on-device ML model development pipeline for a marquee automotive partner. Translate ambiguous feature requests into concrete fine-tuning requirements, generate and wrangle large-scale training data, and run continuous training and evaluation cycles through major software releases. Deliver production-ready model checkpoints with clear dashboards, analyses, and documentation, while maintaining reliable audio-to-function-calling tool use across supported languages.

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FursaFursa
Liquid AI
Liquid AI
1 month ago

Member of Technical Staff - Embedded ML Engineer (Audio/Omni)

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI
Last checked: 17 hours agoStatus: Live

Job Summary

Build and own an end-to-end on-device ML model development pipeline for a marquee automotive partner. Translate ambiguous feature requests into concrete fine-tuning requirements, generate and wrangle large-scale training data, and run continuous training and evaluation cycles through major software releases. Deliver production-ready model checkpoints with clear dashboards, analyses, and documentation, while maintaining reliable audio-to-function-calling tool use across supported languages.
Location: San Francisco
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Translate ambiguous partner feature specs into concrete model training requirements.
  • •Own the fine-tuning recipe for an on-device audio-to-function-calling model and ensure accurate, reliable tool calling across supported languages.
  • •Generate, clean, analyze training data and build/maintain large-scale data pipelines that feed training.
  • •Run training and evaluation cycles against partner requirements continuously through major software releases.
  • •Create polished, partner-facing deliverables including dashboards, analyses, documentation, and model checkpoints.

Pay and Benefits

Equity and Bonus:Equity
Perks:Health InsuranceDentalVision401kPaid Leave

Key Requirements

  • •Hands-on machine learning experience (roughly 2+ years; open to exceptional early-career candidates with strong internship track records).
  • •Personally trained models end-to-end across modalities (computer vision, ADAS, LLMs, audio); building apps around model APIs does not qualify.
  • •Experience with large-scale data pipelines and wrangling large volumes of data.
  • •Experience in automotive, embedded-device, or on-device ML contexts with first-principles reasoning about those environments.
  • •Strong communication skills for a client-facing role.
Experience:2+ yearsAutomotiveEmbedded-device MLOn-device MLMachine learning
Skills:CommunicationClient-ready communicationFirst-principles reasoningData wranglingOwnership

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
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