Embedded ML Engineer — On-Device Audio

Applied Methods Ltd; San Francisco (CA); Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

End-to-end ownership

Equity in unicorn-stage company

Medical, dental, and vision premiums

401(k) matching up to 4%

Unlimited PTO & Refill Days

Job summary

Liquid AI in San Francisco is seeking an Embedded ML Engineer to own the end-to-end model development pipeline for on-device audio-to-function-calling. You will translate partner specs into training requirements, build robust data pipelines, and train/evaluate models across major software releases.

You will generate data, refine fine-tuning recipes, and deliver dashboards and documentation for partner teams, while maintaining high urgency and strong communication with stakeholders.

Qualifications

• Hands-on ML experience with end-to-end training.
• Experience with large-scale data pipelines and wrangling data.
• Background in automotive, embedded-device, or on-device ML contexts.
• Strong client-facing communication skills.

Responsibilities

• Join partner calls, translate feature specs into concrete model training requirements.
• Own the core fine-tuning recipe for an on-device audio-to-function-calling model.
• Generate, clean, and analyze training data; build and maintain large-scale data pipelines for training.
• Run training and evaluation cycles against partner requirements across major software releases.
• Make fast-moving work presentable: dashboards, analyses, documentation, and partner-facing deliverables.
• Progressively take ownership of the end-to-end model development pipeline from spec intake to delivered checkpoints.

Skills

Hands-on ML

Large-scale data pipelines

Embedded/on-device ML

Job description

Liquid AI in San Francisco is seeking an Embedded ML Engineer to own the end-to-end model development pipeline for on-device audio-to-function-calling. You will translate partner specs into training requirements, build robust data pipelines, and train/evaluate models across major software releases.

You will generate data, refine fine-tuning recipes, and deliver dashboards and documentation for partner teams, while maintaining high urgency and strong communication with stakeholders.