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Applied Engineer Jobs in Florida (NOW HIRING)

Project Developer

Tampa, FL · On-site

$90K - $153K/yr

Daikin Applied is seeking a Project Developer for our Tampa office. You will have the ability to make an impact and shape your career with a company that is passionate about growth in supporting the ...

This role combines engineering knowledge with instructional design expertise to create curriculum ... Collaborate closely with Applied Content Engineers to ensure technical accuracy and relevance

Principal Engineer, Electrical

Lake Mary, FL · On-site

$121K - $148K/yr

Proficiency with mathematical concepts including geometry, trigonometry, statistics, and applied engineering calculations. * Ability to solve complex technical problems in situations with limited ...

Sales Engineer

Orlando, FL · On-site

$80K - $100K/yr

Sales Engineer Job Location: Orlando FL Operating Company: Stan Weaver & Company Inc. FLSA Status ... Serve as lead contact for all applied sales opportunities * Perform in estimator capacity (as ...

Sales Engineer

Orlando, FL · On-site

$80K - $100K/yr

Sales Engineer Job Location: Orlando FL Operating Company: Stan Weaver & Company Inc. FLSA Status ... Serve as lead contact for all applied sales opportunities * Perform in estimator capacity (as ...

Opendoor is on a mission to enhance homeownership and is seeking an Applied Scientist to innovate ... Required : • Strong software engineering and coding skills in Python, with experience ...

Showing results 41-60

Applied Engineer information

See Florida salary details

$7

$35

$65

How much do applied engineer jobs pay per hour?

As of Aug 15, 2026, the average hourly pay for applied engineer in Florida is $35.19, according to ZipRecruiter salary data. Most workers in this role earn between $26.78 and $45.43 per hour, depending on experience, location, and employer.

What is an applied engineer?

Applied engineers are professionals who use principles of engineering, mathematics, and science to solve practical problems and improve processes in various industries. Unlike theoretical engineers, applied engineers focus on implementing and optimizing technology, equipment, and systems in real-world settings. They often work in manufacturing, product development, quality control, and operations, bridging the gap between design and production. Applied engineers are skilled in troubleshooting, project management, and applying technical knowledge to enhance efficiency and innovation.

How do applied engineers typically collaborate with cross-functional teams during project development?

Applied Engineers often play a central role in project development by bridging the gap between design concepts and practical implementation. They work closely with teams from R&D, manufacturing, and quality assurance to ensure that solutions are both innovative and feasible. Regular meetings, collaborative problem-solving sessions, and clear communication are essential to address technical challenges and align project goals. This collaborative environment not only enhances project outcomes but also provides opportunities for Applied Engineers to learn from other disciplines and advance their careers.

What are the key skills and qualifications needed to thrive as an applied engineer?

To thrive as an Applied Engineer, you need a strong background in engineering principles, problem-solving, and project management, typically supported by a degree in engineering or a related field. Familiarity with CAD software, manufacturing systems, and quality control tools, as well as certifications like Six Sigma or Lean, are commonly required. Strong analytical thinking, effective communication, and teamwork skills help distinguish top performers in this role. These abilities ensure efficient project execution, innovative solutions, and successful collaboration within multidisciplinary teams.

What jobs can you get with applied engineering?

Applied engineers can pursue roles such as product development engineer, systems engineer, manufacturing engineer, or research engineer. These positions often require skills in problem-solving, technical knowledge, and proficiency with tools like CAD software or programming languages, and may involve working in industries like aerospace, automotive, or electronics.

What are the most commonly searched types of Applied Engineer jobs in Florida?

The most popular types of Applied Engineer jobs in Florida are:

What cities in Florida are hiring for Applied Engineer jobs?

Cities in Florida with the most Applied Engineer job openings:

Infographic showing various Applied Engineer job openings in Florida as of August 2026, with employment types broken down into 90% Full Time, 5% Part Time, and 5% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $73,189 per year, or $35.2 per hour.

Senior Software Engineer Applied AI

Advanced Monitored Caregiving Inc.

Tallahassee, FL • Remote

$116K - $153K/yr

Full-time

Re-posted yesterday


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.