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Remote React Native Jobs in Wisconsin (NOW HIRING)

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How much do remote react native jobs pay per hour?

As of Aug 14, 2026, the average hourly pay for remote react native in Wisconsin is $55.53, according to ZipRecruiter salary data. Most workers in this role earn between $41.73 and $66.97 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the remote React Native position, and why are they important?

To thrive as a Remote React Native developer, you need strong proficiency in JavaScript, React Native, and mobile application development principles, typically backed by relevant experience or a degree in computer science. Familiarity with tools like Git, code versioning systems, mobile debugging platforms, and commonly required certifications such as React Native or JavaScript-related certificates are valuable. Excellent communication, self-motivation, and problem-solving abilities are crucial for collaborating effectively in distributed teams. These skills ensure seamless project delivery, high-quality code, and successful remote team integration.

What is a remote React Native?

A Remote React Native job involves developing mobile applications using the React Native framework while working from a remote location. Developers in this role build cross-platform apps for iOS and Android using JavaScript and React. Responsibilities typically include writing clean code, debugging issues, and collaborating with teams through online communication tools. Remote React Native developers need strong problem-solving skills and familiarity with mobile app development best practices.

What does a typical day look like for a remote React Native developer?

A typical day for a Remote React Native developer involves writing and testing code for mobile apps, collaborating with designers and backend developers through online meetings or chat tools, and participating in code reviews or daily stand-ups. Most developers spend significant time problem-solving and implementing new features or fixing bugs while keeping up to date with best practices in mobile development. Communication is primarily online, requiring clear documentation and regular updates to the team. You’ll also coordinate closely with project managers or stakeholders to clarify requirements and ensure project milestones are met.

What are the most commonly searched types of React Native jobs in Wisconsin?

The most popular types of React Native jobs in Wisconsin are:

What job categories do people searching Remote React Native jobs in Wisconsin look for?

The top searched job categories for Remote React Native jobs in Wisconsin are:

What cities in Wisconsin are hiring for Remote React Native jobs?

Cities in Wisconsin with the most Remote React Native job openings:

Infographic showing various Remote React Native job openings in Wisconsin as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 14% Part Time, 1% Temporary, and 6% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $115,501 per year, or $55.5 per hour.

Senior Software Engineer Applied AI

Advanced Monitored Caregiving Inc.

Madison, WI • Remote

$123K - $162K/yr

Full-time

Re-posted 21 hours 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.