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Remote Audio Post Production Internships Jobs (NOW HIRING)

TEKsystems

Creative Dubbing Director

Seattle, WA · On-site +1

$25 - $28/hr

Similar audio/video post-production platforms * Bachelor's degree in a creative discipline or ... Work Environment * 100% remote position * Standard Monday through Friday business hours

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Remote Audio Post Production Internships information

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$11K

$48.3K

$126.5K

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

As of Sep 2, 2026, the average yearly pay for remote audio post production internships 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 a remote audio post production internship?

Remote Audio Post Production Internships are positions that allow interns to gain hands-on experience in editing, mixing, and mastering audio content for various media projects, all while working from a remote location. Interns typically work with digital audio workstations (DAWs) and collaborate with producers, sound designers, and other professionals online. These internships provide valuable industry skills, exposure to real-world projects, and networking opportunities, making them ideal for students or recent graduates interested in a career in audio production.

What are the key skills and qualifications needed to thrive as a remote audio post production intern?

To thrive as a Remote Audio Post Production Intern, you need a basic understanding of audio editing, sound design, and familiarity with industry-standard audio production concepts, often gained through coursework or related experience. Proficiency with digital audio workstations (DAWs) like Pro Tools, Adobe Audition, or Logic Pro, and the ability to use audio plugins and remote collaboration tools is typically required. Strong attention to detail, time management, and effective communication are crucial soft skills for collaborating with team members and meeting project deadlines. These skills are important to ensure high-quality audio deliverables and seamless collaboration in a remote work environment.

What are some common challenges faced by interns in remote audio post production roles, and how can they be addressed?

Remote audio post production interns often encounter challenges such as managing communication across time zones, accessing large project files, and receiving timely feedback. To address these, it's helpful to establish clear communication channels with your team, utilize cloud-based file sharing platforms, and proactively schedule regular check-ins with supervisors. Embracing collaboration tools and maintaining organized project files can also streamline workflow and enhance your learning experience.

What is the difference between Remote Audio Post Production Internships vs Remote Audio Editing Internships?

AspectRemote Audio Post Production InternshipsRemote Audio Editing Internships
Required SkillsBasic audio editing, sound design, familiarity with DAWsAudio editing, noise reduction, track synchronization
Work EnvironmentRemote, collaborative with post-production teamsRemote, focused on editing tasks
Industry UsageUsed in film, TV, and media post-productionPrimarily in media, advertising, and content creation

Remote Audio Post Production Internships encompass a broader range of post-production tasks, including sound design and mixing, while Remote Audio Editing Internships focus specifically on editing audio tracks. Both roles require familiarity with digital audio workstations and are commonly offered remotely within the media industry. The main difference lies in the scope of responsibilities, with post production internships offering a more comprehensive experience.

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Remote Audio Post Production Internships jobs near you

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 4 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