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Applied Ai Engineer Jobs in Florida (NOW HIRING)

Uloop Inc.

Applied AI Engineer

Miami, FL · On-site

$90 - $120/hr

The Role We are looking for a pragmatic Applied AI Engineer to join our engineering team. The role is not about training models and does not involve academic Machine Learning research. It is about ...

Material Bank

Applied AI Engineer

Boca Raton, FL

About the role As an Applied AI Engineer, you will drive the design, build, and deployment of next-generation AI-powered experiences across Material Bank's platform. You will work as part of the team ...

CYNET SYSTEMS

Applied AI Engineer

Sunrise, FL · On-site

$50 - $55/hr

Experience with generative AI and prompt engineering. * Experience in continuous integration/continuous deployment pipelines and containerized deployments. * Strong attention to detail and commitment ...

Deloitte

Director, Applied AI Engineering

Tampa, FL · On-site

Prior experience using methodologies & tools such as XP, Lean, DevSecOps, SRE, ADO, GitHub ... As a Director, Applied AI Engineering , you will shape and own the engineering strategy and ...

Inficare Technologies

AI Engineer

Sunrise, FL · On-site

As an Applied AI Engineer, you will build those agents, skills, and AI-powered features at scale. Key Responsibilities * Develop, deploy, and refine AI-driven solutions integrating generative AI ...

PODS

Engineer IV - Applied AI

Clearwater, FL · On-site

Data Integration & Engineering • Develop and maintain integrations between AI solutions ... to applied AI technologies and emerging industry trends. • Support pilot programs, proofs of ...

American Express

AI Engineer II

Sunrise, FL · On-site

$89K - $150K/yr

Use LLMs, GenAI, or applied machine learning to build and run large-scale AI solutions. * Improve ... Work closely with product, engineering, and business teams to turn complex problems into effective ...

JPMorgan Chase & Co.

Applied AI/ML Lead

Tampa, FL · On-site

As Applied AI/ML Lead within Commercial & Investment Bank with the Healthcare Provider team, you ... Build and manage a team of ML engineers and applied scientists, fostering a culture of ...

JPMorgan Chase & Co

Applied AI/ML Lead

Tampa, FL

As Applied AI/ML Lead within Commercial & Investment Bank with the Healthcare Provider team, you ... Build and manage a team of ML engineers and applied scientists, fostering a culture of ...

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Applied Ai Engineer information

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

To thrive as an Applied AI Engineer, you need strong proficiency in programming (especially Python), machine learning algorithms, statistics, and a relevant degree in computer science or a related field. Familiarity with frameworks like TensorFlow or PyTorch, experience with cloud platforms (such as AWS or Azure), and knowledge of data management tools are typically required. Excellent problem-solving, communication, and teamwork skills help you translate complex models into real-world solutions and collaborate across disciplines. These competencies ensure you can effectively develop, deploy, and maintain AI systems that drive business value.

What are some common challenges applied AI engineers face when deploying AI models into production environments?

Applied AI Engineers often encounter challenges such as ensuring models perform consistently on real-world data, optimizing models for speed and scalability, and integrating AI solutions with existing systems. Managing data privacy, monitoring for model drift, and maintaining robust documentation are also key concerns. Collaboration with DevOps, data engineering, and product teams is essential to address these challenges effectively and deliver reliable AI-driven solutions.

What is the difference between Applied Ai Engineer vs Data Scientist?

AspectApplied Ai EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; experience with AI frameworksBachelor's or Master's in CS, Statistics, or related fields; strong analytical skills
Work EnvironmentDevelops and deploys AI models in production environmentsAnalyzes data to extract insights and build predictive models
Industry UsageUsed in tech, healthcare, finance for deploying AI solutionsUsed across industries for data analysis and modeling

Applied Ai Engineers focus on implementing and deploying AI models in real-world applications, while Data Scientists primarily analyze data to generate insights and build predictive models. Both roles require similar educational backgrounds but differ in their core responsibilities and work environments.

How much does an applied AI engineer make?

An applied AI engineer's salary varies based on experience, location, and industry, but typically ranges from $80,000 to $150,000 annually. Senior roles or those with specialized skills in machine learning, deep learning, and programming languages like Python or TensorFlow tend to earn higher salaries.

What does an applied AI engineer do?

An applied AI engineer develops and implements artificial intelligence models and algorithms to solve real-world problems. They work with data, machine learning frameworks, and programming languages like Python or TensorFlow to create practical AI solutions for businesses or products.

What are popular job titles related to Applied Ai Engineer jobs in Florida?

For Applied Ai Engineer jobs in Florida, the most frequently searched job titles are:

What job categories do people searching Applied Ai Engineer jobs in Florida look for?

The top searched job categories for Applied Ai Engineer jobs in Florida are:

What cities in Florida are hiring for Applied Ai Engineer jobs?

Cities in Florida with the most Applied Ai Engineer job openings:

Applied Ai Engineer jobs near you
Infographic showing various Applied Ai Engineer job openings in Florida as of August 2026, with employment types broken down into 78% Full Time, 20% Part Time, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution.

Applied AI Engineer

Uloop Inc.

Miami, FL • On-site

$90 - $120/hr

Other

Posted 12 days ago

Job description

The Role

We are looking for a pragmatic Applied AI Engineer to join our engineering team. The role is not about training models and does not involve academic Machine Learning research. It is about building the rails that make AI usable in a high‑stakes financial environment. You will bridge the gap between our robust C#/.NET architecture and the probabilistic world of LLMs.

The Challenge

Title and Escrow is a document‑heavy industry with zero room for error. Your mission is to use AI to clean up the messiness of real‑world real estate data.

  • Structured Data Extraction: Converting messy, unstructured data (like emails, PDFs, documents) from various sources into strictly validated JSON schemas with as close to 100% accuracy as possible.
  • Escrow Automation: Designing workflows that reduce human intervention by 50% by intelligently routing tasks based on AI analysis.
  • Fraud Detection: Implementing deterministic logic checks on bank and financial documents to detect fraud patterns before they happen.
What You’ll Do
  • Engineer the Integration: Write production‑grade code that interacts with external AI APIs.
  • Prompt Engineering as Code: Version, test, and optimize prompts. Define strict schemas to ensure the AI speaks the language of our internal tools.
  • Orchestrate & Validate: Build logic that parses AI responses, validates them against our database (MongoDB), and flags inconsistencies before they reach the user.
  • Full‑Stack Implementation: Visualize AI‑aided services and data for user review and approval.
  • Collaborate: Work closely with senior engineers and product owners to translate complex Title & Escrow schemas into technical constraints that an AI can understand.
What You’ll Bring
  • Developer DNA: Software engineer first with strong experience in Python (C#/.NET is an advantage) and deep programming knowledge.
  • Applied AI Experience: Integrated LLMs into applications via API. Experience with models, AI frameworks, workflows, AI agent building, and orchestration. Understand context windows, token limits, temperature, and guardrails.
  • Data Handling: Experience with complex data structures.
  • The Glue Mindset: Write code that connects services (AWS, AI APIs, Database) to enable seamless features.
  • Collaborative Autonomy: Own the AI domain while embedded in a senior engineering team that provides architecture, code reviews, and best practices.
Nice to Have
  • Experience with AWS infrastructure.
  • Familiarity with the US Real Estate, Title, or Escrow process.
What We Offer

Working in a transparent environment that focuses on solving problems and getting things done. The opportunity to work with very smart and driven people. The ability to grow your talents and career in a high‑growth sector. A remuneration package that is based on the candidate's motivation, skills, and experience.

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ULoop logo

About ULoop

Sourced by ZipRecruiter

Industry

Internet and it

Company size

1 - 10 Employees

Headquarters location

Nashville, TN, US

Year founded

2007

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