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Remote Non Voice Jobs in Wisconsin (NOW HIRING)

Remote Non Voice information

See Wisconsin salary details

$5

$48

$77

How much do remote non voice jobs pay per hour?

As of Aug 18, 2026, the average hourly pay for remote non voice in Wisconsin is $48.62, according to ZipRecruiter salary data. Most workers in this role earn between $39.57 and $60.67 per hour, depending on experience, location, and employer.

What is a remote non voice?

A Remote Non Voice job is a work-from-home position that does not require voice communication, such as phone calls or video meetings. These roles typically involve tasks like data entry, chat support, email handling, content moderation, and transcription. They are ideal for individuals who prefer written communication and have strong typing and organizational skills. Many companies hire for these roles in industries like customer service, e-commerce, and administrative support.

What does a remote non voice do?

A Remote Non Voice employee typically manages customer inquiries, processes orders, or handles support requests via email, chat, or online tickets. Daily responsibilities often include responding to customer messages, updating system records, and resolving issues according to company guidelines. While the job is largely independent, team members regularly communicate through messaging platforms, project management tools, and occasional video meetings to coordinate on complex cases or share updates. Collaboration ensures that service quality remains consistent and that team goals are met. This supportive virtual environment helps remote employees stay connected and effective in their roles.

What are the key skills and qualifications needed to thrive in the remote non voice position?

To excel as a Remote Non Voice professional, you need excellent written communication skills, strong attention to detail, and basic computer literacy, often supported by at least a high school diploma or equivalent. Familiarity with customer support platforms such as Zendesk, CRM systems, and proficiency in office software are commonly needed for this role. Being highly organized, self-motivated, and able to manage time independently are standout qualities. These abilities are crucial for efficiently handling customer queries, maintaining service accuracy, and thriving in a remote, self-directed setting.

What are popular job titles related to Remote Non Voice jobs in Wisconsin?

For Remote Non Voice jobs in Wisconsin, the most frequently searched job titles are:

What cities in Wisconsin are hiring for Remote Non Voice jobs?

Cities in Wisconsin with the most Remote Non Voice job openings:

Infographic showing various Remote Non Voice job openings in Wisconsin as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 16% Part Time, 3% Contract, and 1% Nights. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution, with an average salary of $101,136 per year, or $48.6 per hour.

Senior Software Engineer Applied AI

Advanced Monitored Caregiving Inc.

Madison, WI • Remote

$123K - $162K/yr

Full-time

Re-posted 4 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.