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Ai Audio Jobs in Raleigh, NC (NOW HIRING)

AV Technician

Raleigh, NC · On-site

$20 - $30/hr

... AV integrated systems including audio, video and control of related equipment. Other ... AI and Automated Employment Decision Tool Policy: . By submitting an application, you are ...

Digital Media Tutor

Durham, NC · Remote

$18 - $40/hr

Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ... graphic design basics, audio production, web content, animation fundamentals, and digital ...

Digital Media Tutor

Raleigh, NC · Remote

$18 - $40/hr

Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ... graphic design basics, audio production, web content, animation fundamentals, and digital ...

Digital Media Tutor

Chapel Hill, NC · Remote

$18 - $40/hr

Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ... graphic design basics, audio production, web content, animation fundamentals, and digital ...

Senior Google CX Engineer (GECX)

Durham, NC · On-site +1

$116K - $146K/yr

Design and implement secure integrations between GECX, Google Cloud AI services and external platforms, including defining and configuring real-time CCaaS audio ingestion methods such as SIPREC and ...

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Ai Audio information

See Raleigh, NC salary details

$28.7K

$82.1K

$166.7K

How much do ai audio jobs pay per year?

As of Jul 17, 2026, the average yearly pay for ai audio in Raleigh, NC is $82,098.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,600.00 and $109,800.00 per year, depending on experience, location, and employer.

How does an AI Audio specialist typically collaborate with other teams during a project?

AI Audio specialists often work closely with product managers, software engineers, and UX designers to integrate audio solutions into products or platforms. Collaboration usually involves joint meetings to define project requirements, frequent communication to troubleshoot integration issues, and sharing feedback to refine audio models. A successful AI Audio professional is proactive in bridging technical and creative perspectives, ensuring that audio features meet user needs and technical standards. This team-oriented environment fosters learning and can open pathways to roles in project leadership or advanced technical development.

What is the difference between Ai Audio vs Voiceover Artist?

AspectAi AudioVoiceover Artist
Required CredentialsTechnical skills, AI and audio editing knowledgeVoice training, acting skills, demo reels
Work EnvironmentDigital, remote, tech-focusedRecording studios, remote, live performances
Industry UsageMedia production, AI development, tech companiesAdvertising, entertainment, media
Search & Comparison IntentTechnical, AI-driven audio solutionsCreative voice work, acting

Ai Audio involves creating audio content using artificial intelligence technology, focusing on automation and digital tools. Voiceover Artists provide human voice recordings for various media, emphasizing performance and acting skills. While Ai Audio is tech-based and automated, Voiceover Artists rely on vocal talent and creativity. Both roles are essential in media production but serve different purposes and skill sets.

Which 3 jobs will survive AI?

Audio engineers, voice actors, and audio editors are likely to continue working alongside AI, as their roles require creativity, nuanced judgment, and human expression that AI cannot fully replicate. Skills in audio production, editing software, and understanding of sound design will remain valuable. These jobs often involve tasks that benefit from human oversight and artistic input, making them more resilient to automation.

How much do AI musicians make?

AI musicians' earnings vary widely depending on their experience, the complexity of projects, and the industry. Freelance AI musicians may earn from a few hundred to several thousand dollars per project, while those working for companies or producing commercial content can earn higher salaries, often ranging from $50,000 to over $100,000 annually. Skills in music production, AI tools, and programming can influence earning potential.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level positions in artificial intelligence, such as AI research directors, senior machine learning engineers, or AI executives, which offer compensation in that range including salary, bonuses, and stock options. These roles often require advanced skills in programming, data analysis, and AI frameworks, along with extensive experience and sometimes advanced degrees. Such salaries are usually found in large tech companies or specialized AI firms.

What are the key skills and qualifications needed to thrive as an AI Audio Engineer, and why are they important?

To thrive as an AI Audio Engineer, you need strong foundations in audio signal processing, machine learning, and computer programming, often supported by a degree in computer science, electrical engineering, or a related field. Familiarity with tools such as Python, TensorFlow or PyTorch, digital audio workstations (DAWs), and version control systems is typically required. Attention to detail, creativity, and effective collaboration are standout soft skills for this role. These skills and qualities are essential for developing innovative audio solutions and ensuring seamless integration of AI technologies in audio applications.

Can I get an AI job with no experience?

Entry-level AI audio jobs often do not require extensive experience and may accept candidates with basic knowledge of audio editing, programming, or machine learning. Developing skills in relevant tools like Python, audio processing software, and understanding AI concepts can improve chances of getting hired. Internships or certification programs can also help build necessary qualifications.

What is an AI Audio Engineer?

An AI Audio Engineer is a professional who uses artificial intelligence and machine learning technologies to develop, enhance, or analyze audio content. Their work may include creating AI-driven tools for music production, speech recognition, audio restoration, or sound synthesis. AI Audio Engineers often collaborate with software developers, musicians, and sound designers to integrate intelligent audio solutions into various applications. This field requires knowledge of audio engineering, signal processing, and programming skills.
What job categories do people searching Ai Audio jobs in Raleigh, NC look for? The top searched job categories for Ai Audio jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Ai Audio jobs? Cities near Raleigh, NC with the most Ai Audio job openings:

Senior Software Engineer Applied AI

Advanced Monitored Caregiving Inc.

Raleigh, NC • Remote

$119K - $157K/yr

Full-time

Posted 2 days ago


Job description

Senior Software Engineer: Applied AI (Voice Agents & ML Systems)

AMC Health · Remote (US) · Full-time

The pitch

We build and operate production AI voice agents that hold real phone conversations in a regulated healthcare setting, plus the machine learning and LLM pipelines around them. This is one seat that spans four disciplines that rarely come together: real-time systems, LLM engineering, traditional machine learning, and serious cloud infrastructure, all in production, all with real consequences. If you are the kind of engineer who gets restless doing one thing, this role is the opposite problem.

What you'll work across

Real-time voice AI

  • Streaming, low-latency speech-to-speech systems built on modern LLMs
  • Telephony and real-time media (call control, live audio streaming)
  • Audio handling and the quirks of real human conversation (interruptions, timing, noise)
  • Concurrency on a latency-sensitive path, where p99 matters and a stall is something a caller hears

LLM engineering

  • Wrapping nondeterministic models in deterministic control so they behave reliably in production
  • Multi-model pipelines, prompt design, and cost/latency budgeting
  • Evaluation harnesses, including LLM-as-judge and automated agent-tests-agent approaches
  • Agentic tooling that gives AI systems safe, structured access to infrastructure

Traditional (non-LLM) machine learning

  • End-to-end ML pipelines: feature engineering, model training, and scheduled inference
  • Imbalanced, messy real-world data; calibration and explainability for non-technical consumers
  • Turning research notebooks into reproducible, auditable production pipelines

Cloud and infrastructure

  • Infrastructure as code across multiple environments (we run on AWS)
  • Managed compute, data, streaming, and orchestration services
  • Security engineering in a regulated setting: encryption, least-privilege access, strict data-handling discipline
  • Observability and telemetry-driven debugging, tracing a production issue from a metric anomaly to root cause

Plus occasional full-stack work on internal tools, and an engineering workflow that leans heavily on AI coding assistants, with human accountability for every change.

What you'll actually do

  • Ship and debug code on a live, real-time voice pipeline where latency and correctness are user-facing
  • Design control systems around LLMs: guardrails, budgets, watchdogs, safe fallbacks
  • Build and operate LLM evaluation and batch-analysis pipelines
  • Own traditional ML workflows from data to scheduled production inference
  • Trace production issues from a metric anomaly to root cause, including building the evidence when the cause is a vendor

Must-haves

  • 7+ years building and operating production backend systems, with strong general-purpose programming skills (we work primarily in Python)
  • Experience running distributed systems in the cloud; comfortable debugging from telemetry to root cause
  • Hands-on production experience with LLMs or generative AI (any provider or framework), plus the judgment to know when not to use a model
  • Working fluency across the traditional machine learning lifecycle (you productionize; you do not need to publish)
  • Disciplined in a regulated environment: small, reviewable changes and careful handling of sensitive data

Nice-to-haves

  • Real-time media or telephony experience
  • Front-end / full-stack ability
  • ML pipeline experience, vector search, or embeddings
  • Fluency with AI coding assistants (our workflows assume them, with human accountability for every change)

How we work

Smallest correct change wins. Every behavior change is validated against the live system. Evidence over opinion in debugging. Code review is rigorous. Safety and privacy gate everything.

Work authorization (no exceptions)

This role is open only to US citizens and lawful permanent residents (Green Card holders). We cannot consider candidates who require visa sponsorship now or in the future, and we are unable to make exceptions of any kind.

How to apply

Please submit both of the following:

  • Your LinkedIn profile URL
  • A phone number where we can reach you

A resume is welcome but optional; the two items above are required.