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Machine Learning Testing Jobs in Florida (NOW HIRING)

Annotate data and support model testing and training. * Support or lead the development of machine-learning detectors and classifiers for sensor data. * Develop, train, test and validate analytical ...

... testing. Every innovation we pursue is driven by one purpose: making personalized medicine more ... Develop and implement AI and machine learning solutions that improve operational efficiency and ...

Senior Software Engineer

Tampa, FL · On-site

$90 - $140/hr

Machine Learning * Unit Testing * Linux Shell Scripting * Version Control (Git) Soft Skills * Communication * Collaboration * Problem-Solving Certifications & Qualifications * Bachelor of Science

Post Doctoral Associate

Gainesville, FL · On-site

$44K - $60K/yr

This position focuses on developing clinically meaningful machine learning models, publishing ... Perform rigorous model evaluation, including external validation, robustness testing, and bias and ...

AI Engineer

Boca Raton, FL · On-site

$50K - $112K/yr

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ... testing, and adversarial benchmarking, to assess reasoning, tool-calling reliability, and output ...

Showing results 41-60

Machine Learning Testing information

See Florida salary details

$10

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How much do machine learning testing jobs pay per hour?

As of Aug 23, 2026, the average hourly pay for machine learning testing in Florida is $17.05, according to ZipRecruiter salary data. Most workers in this role earn between $14.71 and $19.04 per hour, depending on experience, location, and employer.

What is a machine learning testing?

A Machine Learning Testing job involves evaluating and validating machine learning models to ensure they function correctly, efficiently, and ethically. This includes testing for accuracy, reliability, bias, and performance under different conditions. Professionals in this role employ techniques such as unit testing, integration testing, data validation, and model performance monitoring. They also work closely with data scientists and engineers to debug issues and improve model robustness. The goal is to ensure that machine learning systems perform as expected and meet business or regulatory requirements.

What are the typical challenges faced by professionals in machine learning testing roles?

Professionals in Machine Learning Testing often encounter challenges such as dealing with non-deterministic model outputs, insufficient or imbalanced datasets, and unclear or evolving testing criteria. They may need to work closely with data scientists and engineers to develop robust test cases and validation methods tailored for dynamic machine learning systems. Staying updated on advancements in testing methodologies and tools is also important, as the field evolves rapidly. Successfully overcoming these challenges leads to higher quality models and more reliable AI solutions for end users.

What are the key skills and qualifications needed to thrive in machine learning testing, and why are they important?

To excel in Machine Learning Testing, you need a solid understanding of machine learning concepts, data analysis, and programming skills in languages like Python, as well as a background in quality assurance or software testing. Familiarity with frameworks such as TensorFlow, PyTorch, automated testing tools, and relevant certifications like ISTQB are highly beneficial. Strong attention to detail, analytical thinking, and effective communication skills help testers identify issues and collaborate with data scientists and developers. These competencies are essential to ensure the reliability, fairness, and accuracy of machine learning models deployed in production environments.

How do I become a machine learning testing?

To become a machine learning testing professional, you typically need a strong background in computer science, programming skills in languages like Python or Java, and knowledge of machine learning frameworks such as TensorFlow or PyTorch. Gaining experience with data analysis, model evaluation, and testing methodologies, along with relevant certifications or training, can improve your qualifications for this role.

What are the most commonly searched types of Machine Learning Testing jobs in Florida?

The most popular types of Machine Learning Testing jobs in Florida are:

Infographic showing various Machine Learning Testing job openings in Florida as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 22% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $35,472 per year, or $17.1 per hour.

Cyber Digital Trust & Online Safety Manager

Deloitte

Lake Mary, FL

Full-time

Re-posted 2 days ago


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 93 frontline employees who took The Breakroom Quiz

45th of 151 rated financial services


Job description

Cyber Digital Trust and Online Safety Manager

The Digital Trust & Online Protection Professional will advise clients in developing, managing, and implementing policies, procedures, and strategies to ensure a safe, compliant, and trustworthy environment for our users. This individual will scale and mature digital trust and safety processes, including content compliance, user protection, and regulatory adherence across our platforms for our clients. Working closely with cross-functional stakeholders, this role will monitor regulatory changes, manage risks, and enhance our organization's approach to content safety, user trust, and online integrity.

Recruiting for this role ends on 12/31/3026.

Work you'll do

As a Manager, Strategy, Growth, and Transformation on the Deloitte Cyber team, you will be responsible for:

  • Designing and executing testing scenarios to identify how prompts or user inputs could be manipulated to generate harmful, misleading, or misaligned generative artificial intelligence outputs.
  • Researching emerging prompt injection, jailbreak, and adversarial testing techniques to evaluate model weaknesses, bias, factual inaccuracy, and misalignment with user intent.
  • Assessing the effectiveness of content moderation systems in detecting unsafe outputs and documenting vulnerabilities, failure patterns, and potential misuse impacts.
  • Recommending improvements to moderation policies, flagging mechanisms, training data, and governance controls based on testing findings.
  • Collaborating with generative artificial intelligence development, content moderation, and cross-functional stakeholders to strengthen security, trust, safety, and responsible use outcomes.
  • Developing multimodal test content and novel prompt manipulation methods to identify failure modes across text and other model inputs.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to mentor and provide clear guidance to others

The team

Enables trust and safety of online communications and digital products, protecting users, consumers, and patients from harm. Enables clients to provide consumer confidence in knowing with whom they are dealing and ensuring the integrity of access to data.

Qualifications

Required:

  • Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Cybersecurity, Linguistics, Psychology, or a related field, or equivalent professional experience
  • 10+ years of experience in threat modeling and simulation, prompt generation and analysis, novel testing, and reporting and improvement
  • Demonstrated hands-on experience, portfolio work, publications, or research in prompt injection, jailbreak testing, model evaluation, adversarial machine learning, multimodal artificial intelligence safety, or generative artificial intelligence vulnerability assessment
  • Ability to travel 25-50%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • Doctor of Philosophy (PhD) in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Cybersecurity, Linguistics, Psychology, or a related field, or equivalent professional experience
  • Specialized training or certifications in generative artificial intelligence red teaming, adversarial machine learning, artificial intelligence security, cybersecurity, responsible artificial intelligence, or artificial intelligence governance
  • Experience designing and operationalizing trust and safety testing programs for large-scale consumer platforms, including escalation workflows, issue triage, and remediation tracking
  • Experience working with product, legal, policy, and engineering stakeholders to translate risk findings into practical platform controls and governance improvements

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $134,500 to $265,100.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

#CyberDTP27

Qualifications:

Cyber Digital Trust and Online Safety Manager

The Digital Trust & Online Protection Professional will advise clients in developing, managing, and implementing policies, procedures, and strategies to ensure a safe, compliant, and trustworthy environment for our users. This individual will scale and mature digital trust and safety processes, including content compliance, user protection, and regulatory adherence across our platforms for our clients. Working closely with cross-functional stakeholders, this role will monitor regulatory changes, manage risks, and enhance our organization's approach to content safety, user trust, and online integrity.

Recruiting for this role ends on 12/31/3026.

Work you'll do

As a Manager, Strategy, Growth, and Transformation on the Deloitte Cyber team, you will be responsible for:

  • Designing and executing testing scenarios to identify how prompts or user inputs could be manipulated to generate harmful, misleading, or misaligned generative artificial intelligence outputs.
  • Researching emerging prompt injection, jailbreak, and adversarial testing techniques to evaluate model weaknesses, bias, factual inaccuracy, and misalignment with user intent.
  • Assessing the effectiveness of content moderation systems in detecting unsafe outputs and documenting vulnerabilities, failure patterns, and potential misuse impacts.
  • Recommending improvements to moderation policies, flagging mechanisms, training data, and governance controls based on testing findings.
  • Collaborating with generative artificial intelligence development, content moderation, and cross-functional stakeholders to strengthen security, trust, safety, and responsible use outcomes.
  • Developing multimodal test content and novel prompt manipulation methods to identify failure modes across text and other model inputs.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to mentor and provide clear guidance to others

The team

Enables trust and safety of online communications and digital products, protecting users, consumers, and patients from harm. Enables clients to provide consumer confidence in knowing with whom they are dealing and ensuring the integrity of access to data.

Qualifications

Required:

  • Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Cybersecurity, Linguistics, Psychology, or a related field, or equivalent professional experience
  • 10+ years of experience in threat modeling and simulation, prompt generation and analysis, novel testing, and reporting and improvement
  • Demonstrated hands-on experience, portfolio work, publications, or research in prompt injection, jailbreak testing, model evaluation, adversarial machine learning, multimodal artificial intelligence safety, or generative artificial intelligence vulnerability assessment
  • Ability to travel 25-50%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • Doctor of Philosophy (PhD) in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Cybersecurity, Linguistics, Psychology, or a related field, or equivalent professional experience
  • Specialized training or certifications in generative artificial intelligence red teaming, adversarial machine learning, artificial intelligence security, cybersecurity, responsible artificial intelligence, or artificial intelligence governance
  • Experience designing and operationalizing trust and safety testing programs for large-scale consumer platforms, including escalation workflows, issue triage, and remediation tracking
  • Experience working with product, legal, policy, and engineering stakeholders to translate risk findings into practical platform controls and governance improvements

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $134,500 to $265,100.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

#CyberDTP27

Education:Bachelor's DegreeEmployment Type:

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