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Numerical Modeling Jobs in Madison, WI (NOW HIRING)

SOL Mental Health

Psychiatric Clinician

Madison, WI · On-site

$145K - $233K/yr

Active NPI number * Experience in direct clinical care * 2+ years of experience providing ... Integrated care model with collaboration across disciplines * Career growth paths and advancement ...

New

Cyod

Account Principal, Work Transformation

Oregon, WI · On-site

$120 - $180/hr

Requisition Number: 105240 Account Principal, Work Transformation Location: You will have the ... Proven ability to navigate complex contracting models and drive services sales from plan to ...

Varsity Tutors

Middle School Math Tutor

Madison, WI · Remote

$18 - $40/hr

Ability to explain number sense, coordinate plane plotting, and mathematical reasoning while ... using visual models and hands-on manipulatives. Guides students through pre-algebra concepts ...

Foth

Lead Hydrogeologist

Madison, WI

$100K - $140K/yr

Demonstrated experience coordinating and executing field characterization programs, including aquifer testing, hydrophysical profiling, groundwater modeling, and numerical analysis * Proven ability ...

Foth

Lead Hydrogeologist

Madison, WI

$100K - $140K/yr

Demonstrated experience coordinating and executing field characterization programs, including aquifer testing, hydrophysical profiling, groundwater modeling, and numerical analysis * Proven ability ...

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All JobsNumerical Modeling JobsNumerical Modeling Jobs in Madison, WI

Numerical Modeling information

See Madison, WI salary details

$27.7K

$57.2K

$61K

How much do numerical modeling jobs pay per year?

As of Aug 9, 2026, the average yearly pay for numerical modeling in Madison, WI is $57,155.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,400.00 and $60,000.00 per year, depending on experience, location, and employer.

What is numerical modeling?

A Numerical Modeling job involves developing and using mathematical models to simulate real-world physical, biological, or engineering systems. Professionals in this field use computational techniques to analyze complex problems, predict behaviors, and optimize designs. They often work with software tools like MATLAB, Python, or specialized simulation programs and apply knowledge from physics, mathematics, and engineering. Numerical modelers are employed in various industries, including aerospace, climate science, finance, and healthcare.

What are the typical daily tasks for someone working in numerical modeling?

Professionals in Numerical Modeling typically spend their days designing and implementing computational models, running simulations, and analyzing data to solve real-world engineering or scientific problems. They often collaborate with other engineers, scientists, or project managers to ensure that models accurately represent complex systems and align with project objectives. Tasks may also include validating models against experimental data, troubleshooting numerical issues, and preparing technical reports or presentations. This role requires a mix of independent research, teamwork, and continuous communication to deliver effective solutions.

What are the key skills and qualifications needed to thrive in numerical modeling, and why are they important?

To excel in Numerical Modeling, a deep understanding of mathematics, physics, and computational methods, often supported by a degree in engineering or science, is essential. Familiarity with programming languages such as Python, MATLAB, or C++, as well as experience with simulation software and numerical analysis tools, is commonly required. Strong problem-solving abilities, attention to detail, and the ability to clearly communicate complex concepts are valuable soft skills in this field. These competencies ensure accurate model development and collaboration within interdisciplinary teams, driving successful real-world solutions.

What jobs use mathematical modeling?

Numerical modeling is used in a variety of jobs such as data scientist, financial analyst, engineer, climate scientist, and operations researcher. These roles involve developing and applying mathematical models to analyze data, optimize processes, or simulate real-world systems, often requiring skills in programming, statistics, and specialized software. Such positions are common in industries like finance, engineering, environmental science, and technology.
What are popular job titles related to Numerical Modeling jobs in Madison, WI? For Numerical Modeling jobs in Madison, WI, the most frequently searched job titles are:
What job categories do people searching Numerical Modeling jobs in Madison, WI look for? The top searched job categories for Numerical Modeling jobs in Madison, WI are:
Numerical Modeling jobs near you
Infographic showing various Numerical Modeling job openings in Madison, WI as of August 2026, with employment types broken down into 84% Full Time, 12% Part Time, and 4% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $57,155 per year, or $27.5 per hour.

Senior Software Engineer Applied AI

Advanced Monitored Caregiving Inc.

Madison, WI • On-site

$150 - $220/hr

Other

Posted 25 days ago

Job description

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

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

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

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