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Full Time Ai Voice Jobs (NOW HIRING)

We're looking for a full-time AI Engineer to help shape and execute Fanatics' AI strategy across ... A front-row seat, and a real voice, in how a global sports and collectibles company adopts AI.

Staff Design Engineer Clerk Chat | Full-time About Clerk Chat Clerk Chat is a conversational AI platform that handles customer communications across SMS, voice, and email channels. Recently Series A ...

Full-time structured scheduling, stable pay with payroll tax withholding, company-provided training ... By applying, you consent to Traba contacting you via text messages and AI voice calls regarding ...

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Full Time Ai Voice information

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$48

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How much do full time ai voice jobs pay per hour?

As of Aug 12, 2026, the average hourly pay for full time ai voice in the United States is $48.17, according to ZipRecruiter salary data. Most workers in this role earn between $39.18 and $60.10 per hour, depending on experience, location, and employer.

How to become a full time AI voice?

To become a full-time AI voice actor or developer, you should develop strong voice modulation and recording skills, familiarize yourself with speech synthesis tools and AI training platforms, and build a portfolio of voice samples. Gaining experience with machine learning concepts and audio editing software can also improve your prospects in this field.

What are some common challenges faced by professionals working full time in AI voice roles, and how can they be addressed?

Full-time AI voice professionals often encounter challenges such as ensuring high accuracy in speech recognition, maintaining natural-sounding speech synthesis, and adapting voice models to diverse accents or languages. Collaboration with linguists, data scientists, and software engineers is vital to address these issues and improve model performance. Keeping up with rapid advancements in AI technology and continuously testing models with real-world data can help professionals stay ahead and deliver high-quality voice solutions.

What are the key skills and qualifications needed to thrive as an AI voice developer?

To thrive as an AI Voice Developer, you need strong programming skills (such as Python), understanding of natural language processing (NLP), and typically a background in computer science or a related field. Familiarity with tools and frameworks like TensorFlow, PyTorch, and speech recognition APIs, as well as experience with cloud platforms, is essential. Creative problem-solving, attention to detail, and effective collaboration are standout soft skills in this role. These skills and qualities are crucial for developing accurate, user-friendly AI voice solutions that meet real-world communication needs.

What is a full time AI voice job?

Full Time AI Voice jobs involve working with artificial intelligence technologies that generate, process, or analyze human speech. Professionals in these roles may develop, train, and optimize AI models for voice recognition, speech synthesis, and natural language processing. These positions often require skills in machine learning, linguistics, and software engineering, and can be found in industries like tech, customer service, and entertainment. The work typically includes designing AI voice assistants, improving speech-to-text accuracy, and creating lifelike synthetic voices for various applications.
More about Full Time Ai Voice jobs
What cities are hiring for Full Time Ai Voice jobs? Cities with the most Full Time Ai Voice job openings:
What are the most commonly searched types of Ai Voice jobs? The most popular types of Ai Voice jobs are:
What states have the most Full Time Ai Voice jobs? States with the most job openings for Full Time Ai Voice jobs include:
What job categories do people searching Full Time Ai Voice jobs look for? The top searched job categories for Full Time Ai Voice jobs are:
Infographic showing various Full Time Ai Voice job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 20% Part Time, and 4% Contract. Highlights an 67% Physical, 4% Hybrid, and 29% Remote job distribution, with an average salary of $100,198 per year, or $48.2 per hour.

Senior Software Engineer Applied AI

Advanced Monitored Caregiving Inc.

Trenton, NJ • Remote

$122K - $162K/yr

Full-time

Posted 28 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.