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Remote Entry Level Audio Post Production Jobs (NOW HIRING)

Innodata Inc.

Audio Engineer

$120K - $160K/yr

Own the end-to-end audio signal chain and post-processing pipeline for all collection programs ... Specify and validate recording setups for vendors and remote contributors (signal-chain testing in ...

AO Globe Life

CSR Entry-Level Remote

Seattle, WA · On-site +1

$100K/yr

We are hiring Remote Entry-Level Managing Agents for a full-time, fully remote role that allows you ... Analyze members' financial situations and explain the advantages of additional benefits products ...

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Remote Entry Level Audio Post Production information

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$11K

$48.3K

$126.5K

How much do remote entry level audio post production jobs pay per year?

As of Jul 10, 2026, the average yearly pay for remote entry level audio post production in the United States is $48,339.00, according to ZipRecruiter salary data. Most workers in this role earn between $26,500.00 and $61,000.00 per year, depending on experience, location, and employer.

What is the difference between Remote Entry Level Audio Post Production vs Remote Audio Editor?

AspectRemote Entry Level Audio Post ProductionRemote Audio Editor
CredentialsBasic audio editing skills, possibly a degree or certification in audio productionSimilar credentials, often with additional focus on editing software proficiency
Work EnvironmentHome studio or remote setup, collaborating with post-production teamsRemote work, often freelance or project-based, using editing software
Industry UsageUsed in film, TV, advertising, and media post-productionPrimarily in media, film, and broadcasting industries

Remote Entry Level Audio Post Production and Remote Audio Editor roles share similar credentials and work environments, focusing on audio editing tasks within media industries. The main difference lies in scope: post production involves broader tasks like sound design and mixing, while audio editing centers on cleaning and assembling audio clips. Both roles are suitable for entry-level candidates seeking remote opportunities in media production.

More about Remote Entry Level Audio Post Production jobs
What cities are hiring for Remote Entry Level Audio Post Production jobs? Cities with the most Remote Entry Level Audio Post Production job openings:
What job categories do people searching Remote Entry Level Audio Post Production jobs look for? The top searched job categories for Remote Entry Level Audio Post Production jobs are:
Remote Entry Level Audio Post Production jobs near you
Infographic showing various Remote Entry Level Audio Post Production job openings in the United States as of July 2026, with employment types broken down into 81% Full Time, 14% Part Time, and 5% Contract. Highlights an 100% Remote job distribution, with an average salary of $48,339 per year, or $23.2 per hour.
Member of Technical Staff - Post Training, Applied (Audio)

Member of Technical Staff - Post Training, Applied (Audio)

Liquid AI, Inc

San Francisco, CA • On-site, Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 10 days ago

Job description

About Liquid AI
Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency, minimal memory usage, privacy, and reliability. We partner with enterprises across consumer electronics, automotive, life sciences, and financial services. We are scaling rapidly and need exceptional people to help us get there.
The Opportunity
LFM2.5-Audio is Liquid's end-to-end multimodal speech and text language model. At 1.5B parameters, it handles speech-to-speech conversation, ASR, and TTS without requiring separate components, making it uniquely suited for real-time, on-device deployment.
We're now bringing this model to enterprise customers. The core challenge: teaching audio models to understand user intents and translate them into structured tool calls. Think voice-driven function calling, where a spoken request triggers the right API, extracts the right parameters, and confirms back to the user in natural speech.
This role sits at the intersection of frontier audio models and real-world deployment. You'll own the applied post-training work that adapts LFM2.5-Audio for customer use cases end-to-end, from data generation through delivery. Unlike most roles that force a trade-off between customer impact and foundational work, this one gives you both: deep ownership over how audio models are adapted, evaluated, and shipped, and a direct line into the evolution of Liquid's post-training and audio stacks.
If you care about data quality, evaluation, and making models actually work in production, this is a chance to shape how applied audio AI is done at a foundation model company.
What We're Looking For
We need someone who:
  • Takes ownership: Owns customer post-training projects end-to-end for audio workloads, from requirements through delivery and evaluation.
  • Thinks end-to-end: Can reason across audio data pipelines, speech-text alignment, model adaptation, and evaluation as a connected system.
  • Is pragmatic: Optimizes for model quality and customer outcomes over publications or theory.
  • Thrives under constraints: On-device, low-latency, memory-limited audio systems excite you. You see constraints as design parameters, not blockers.

The Work
  • Act as the technical owner for enterprise audio post-training engagements.
  • Translate customer requirements into concrete post-training specifications and workflows for LFM2.5-Audio and future audio models.
  • Design and build function calling capabilities for audio models: training models to map spoken user intents to structured tool calls (API invocations, parameter extraction, confirmation flows).
  • Design and execute data generation pipelines for speech-to-speech and text-to-text training, including synthetic dialogue, function calling examples, and intent-action pairs.
  • Run supervised fine-tuning, preference alignment, and reinforcement learning workflows on audio language models.
  • Design task-specific evaluations for audio function calling (intent recognition accuracy, parameter extraction, end-to-end task completion) and feed learnings back into core post-training pipelines.

Desired Experience
Must-have:
  • Hands-on experience with post-training for language models (SFT, preference alignment, and/or RL).
  • Experience with data generation and evaluation pipelines for LLM or audio model training.
  • Strong intuition for data quality and evaluation design.
  • Familiarity with function calling, tool use, or structured output training for language models.

Nice-to-have:
  • Experience with speech or audio language models (speech-to-speech, ASR, TTS, or multimodal audio-text systems).
  • Prior exposure to customer-facing or applied ML delivery environments.
  • Experience with alignment or RL techniques beyond basic supervised fine-tuning.
  • Familiarity with on-device or low-latency inference constraints.

What Success Looks Like (Year One)
  • Independently owns and delivers enterprise audio post-training projects with minimal oversight.
  • Has built and shipped function calling capabilities that reliably translate spoken user intents into tool calls for production use cases.
  • Is trusted by customers as the technical owner, demonstrating strong judgment and delivery quality.
  • Has made durable contributions to Liquid's general-purpose post-training and audio pipelines by feeding applied learnings back into baseline model development.

What We Offer
  • Real ML work: You will fine-tune audio and speech models, build audio data pipelines, and ship solutions to enterprise customers under real-time on-device constraints.
  • Compensation: Competitive base salary with equity in a unicorn-stage company
  • Health: We pay 100% of medical, dental, and vision premiums for employees and dependents
  • Financial: 401(k) matching up to 4% of base pay
  • Time Off: Unlimited PTO plus company-wide Refill Days throughout the year

Apply