2

Podcast Audio Engineer Remote Jobs in Indiana (NOW HIRING)

Podcast Audio Engineer Remote information

What are some common challenges faced by remote Podcast Audio Engineers, and how can they be addressed?

Remote Podcast Audio Engineers often encounter challenges such as coordinating with hosts and guests across different time zones, maintaining consistent audio quality with varied recording setups, and managing real-time technical troubleshooting from a distance. Effective communication, using collaborative tools (like shared project management platforms and cloud storage), and setting up clear guidelines for recording can help address these issues. Regular check-ins with the production team and investing in reliable remote recording software are also key to ensuring smooth workflow and high-quality episodes.

What are Podcast Audio Engineers (Remote)?

Podcast Audio Engineers (Remote) are professionals who specialize in recording, editing, mixing, and enhancing audio specifically for podcasts, all while working from a remote location. Their responsibilities include cleaning up audio tracks, balancing sound levels, adding effects or music, and ensuring the final product meets broadcast quality standards. Working remotely, they collaborate with hosts, producers, and other team members using digital tools and cloud-based platforms. Their expertise ensures that listeners enjoy clear, engaging, and professional-sounding podcasts.

How much do podcast engineers make?

Podcast audio engineers typically earn between $40,000 and $80,000 annually, depending on experience, location, and whether they work freelance or full-time. Skilled engineers with proficiency in editing software and audio equipment can command higher salaries, especially in remote or specialized roles.

What engineer makes $500,000 a year?

In the field of podcast audio engineering, earning $500,000 annually is uncommon and typically requires extensive experience, high-profile projects, or ownership of a successful business. Most audio engineers earn significantly less, with top professionals in specialized or executive roles potentially reaching high six-figure incomes. Achieving such a salary often involves additional skills, certifications, or entrepreneurial ventures beyond standard audio engineering work.

Is there a high demand for audio engineers?

The demand for audio engineers, including those working on podcasts, is growing due to the increasing popularity of digital media and content creation. Remote audio engineering roles are expanding as companies seek skilled professionals with proficiency in editing software and audio production tools. Job opportunities are available across various industries, with a focus on versatile skills and experience.

What are the key skills and qualifications needed to thrive as a Podcast Audio Engineer in a remote setting, and why are they important?

To excel as a Podcast Audio Engineer remotely, you need expertise in audio editing, mixing, and mastering, often backed by experience or a relevant degree in audio production. Familiarity with digital audio workstations (DAWs) like Adobe Audition, Pro Tools, or Audacity, and proficiency with remote collaboration tools are typically required. Outstanding time management, communication skills, and attention to detail help you meet deadlines and collaborate effectively with hosts and producers. These competencies ensure the delivery of high-quality audio content and seamless remote production workflows.

What is the difference between Podcast Audio Engineer Remote vs Podcast Sound Technician?

AspectPodcast Audio Engineer RemotePodcast Sound Technician
CredentialsAudio engineering certification, relevant experienceAudio or sound technology background, certifications optional
Work EnvironmentRemote, home studio setupStudio or remote, depending on employer
Industry UsageCommon in podcast production companies, freelancersUsed in live events, studio recordings, podcast setups
Search & Comparison IntentHigh overlap in audio skills, remote work focusSimilar audio skills, often in different settings

The main difference is that Podcast Audio Engineer Remote typically involves remote audio editing, mixing, and mastering for podcasts, often requiring specialized certifications. Podcast Sound Technicians may work in studio or live environments, focusing on sound setup and recording. Both roles share core audio skills but differ mainly in work setting and specific responsibilities.

Can you work from home as an audio engineer?

Podcast audio engineers can often work from home, especially when editing, mixing, and mastering audio files using digital audio workstations and remote collaboration tools. However, some roles may require on-site presence for recording sessions or equipment setup, depending on the employer and project needs.
What are popular job titles related to Podcast Audio Engineer Remote jobs in Indiana? For Podcast Audio Engineer Remote jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Podcast Audio Engineer Remote jobs in Indiana look for? The top searched job categories for Podcast Audio Engineer Remote jobs in Indiana are:
What cities in Indiana are hiring for Podcast Audio Engineer Remote jobs? Cities in Indiana with the most Podcast Audio Engineer Remote job openings:

Senior Software Engineer Applied AI

Advanced Monitored Caregiving Inc.

Indianapolis, IN • Remote

$117K - $154K/yr

Full-time

Posted 9 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.