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Machine Learning Engineer Jobs in Jacksonville, FL

Master's degree in Computer Science or a related discipline with a focus on AI or machine learning is preferred. * 3 to 5 years of software engineering experience, including hands-on development of ...

... machine learning, or data-focused delivery work. • Experience using Jira, Azure DevOps, Smartsheet, MS Project, or similar delivery tools. • Experience supporting Agile, software, engineering ...

Within our Data and Analytics Engineering practice, you will apply data, algorithms, and software engineering to build and deploy AI and Machine Learning solutions at scale. As a Director, you will ...

Agile Delivery Manager

Jacksonville, FL · On-site

$90K - $115K/yr

... AI, machine learning, software, and cross-functional product work. * Operate at both the Agile team level and the project delivery level. * Collaborate across Product, Engineering, Data Science ...

Showing results 41-60

Machine Learning Engineer information

See Jacksonville, FL salary details

$28.3K

$115.8K

$174K

How much do machine learning engineer jobs pay per year?

As of Aug 8, 2026, the average yearly pay for machine learning engineer in Jacksonville, FL is $115,793.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,300.00 and $139,400.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a machine learning engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Jacksonville, FL? The most popular types of Machine Learning Engineer jobs in Jacksonville, FL are:
What are popular job titles related to Machine Learning Engineer jobs in Jacksonville, FL? For Machine Learning Engineer jobs in Jacksonville, FL, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Jacksonville, FL look for? The top searched job categories for Machine Learning Engineer jobs in Jacksonville, FL are:
What cities near Jacksonville, FL are hiring for Machine Learning Engineer jobs? Cities near Jacksonville, FL with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Jacksonville, FL as of July 2026, with employment types broken down into 1% As Needed, 71% Full Time, 24% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $119,313 per year, or $57.4 per hour.

Cyber - SecOps - Consultant

Deloitte

Jacksonville, FL

Full-time

Posted 8 days ago


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

45th of 150 rated financial services


Job description

If you're looking for an opportunity to work at the intersection of cybersecurity, data, and artificial intelligence, Deloitte's Cyber Defense & Resilience team offers the scale, complexity, and growth environment to build your career. In this role, you will support organizations as they modernize security operations through advanced analytics, cyber data engineering, and AI-enabled capabilities. You will work with leading technologies and help clients strengthen cyber defense while enabling innovation across the enterprise.

Recruiting for this role ends on 12/31/2026.

Work you'll do

As a Cyber SecOps Consultant on the Cyber Defense & Resilience team, you will be responsible for...

  • Supporting the design and modernization of cyber data and analytics programs that improve organizational intelligence and enable scalable delivery models
  • Developing and applying analytics, machine learning, and data science techniques to cyber use cases across security operations, threat detection, and incident response
  • Working with technologies such as Databricks for Cyber, AWS Security Lake, Google SecOps, Splunk, CrowdStrike, and Palo Alto Networks to support cyber data platforms and operational outcomes
  • Assisting with the maintenance, enhancement, governance, and administration of data platforms and applications using standardized, automated, and AI-enabled DataOps capabilities
  • Contributing to AI and analytics initiatives by helping clients experiment, operationalize, and scale solutions using cyber and information technology telemetry data

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 provide clear guidance to others

The team

Cyber Defense & Resilience is an integrated team of security and data technologists working at the intersection of cybersecurity, advanced cyber data engineering, and the use of artificial intelligence and machine learning for cyber defense and operations. The team serves as a trusted advisor and managed service provider, bringing capability and capacity across security data modernization, DataOps, AI, and machine learning to address cyber-specific challenges.

Cyber Detect & Respond practitioners work with clients to modernize large-scale cyber data and analytics programs, support embedded and as-a-service delivery models, and strengthen day-to-day security operations. The team also helps clients harness technologies such as Databricks for Cyber, AWS Security Lake, Google SecOps, Splunk, CrowdStrike, and Palo Alto Networks while advancing AI and analytics capabilities through scalable assets, curated datasets, and operational experience.

Qualifications

Required:

  • 2+ years of analytics consulting or industry experience
  • 2+ years of experience with artificial intelligence development tools, including vector databases such as Pinecone or Elastic, and development frameworks such as LangChain or CrewAI
  • 2+ years of experience in statistical analysis, machine learning, and data mining
  • 2+ years of experience using statistical computer languages such as Python, Structured Query Language (SQL), R, or SAS to prepare data for analysis, perform exploratory analysis, generate features, and support data science workflows
  • 2+ years of experience using cloud-based cybersecurity platforms such as Google SecOps, Amazon Web Services (AWS), or Microsoft Azure
  • 1+ years of experience with security operations center threat hunting and incident response
  • Experience supporting at least one full lifecycle analytics engagement across strategy, design, and implementation
  • Bachelor's degree in Engineering, Mathematics, or Statistics, or 4 years of equivalent professional experience
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • Experience architecting, designing, developing, and deploying enterprise data science solutions that include natural language processing (NLP), chatbots, virtual assistants, computer vision, cognitive services, and big data tools used to manage large datasets
  • Experience applying artificial intelligence (AI), machine learning (ML), and advanced data engineering to cybersecurity use cases, including detection and cyber threat response acceleration
  • Experience parsing and normalizing cybersecurity or information technology telemetry datasets
  • Experience using Python machine learning and deep learning frameworks and libraries, including PyTorch, Keras, TensorFlow, scikit-learn, NumPy, and SciPy
  • Experience designing and implementing Apache open-source frameworks, including Kafka, Storm, and Spark, to support end-to-end data management lifecycle activities
  • Experience managing multiple concurrent task assignments and developing presentation materials using Microsoft Visio and Microsoft PowerPoint

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 $82,600 - $162,800.

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.


Qualifications:

If you're looking for an opportunity to work at the intersection of cybersecurity, data, and artificial intelligence, Deloitte's Cyber Defense & Resilience team offers the scale, complexity, and growth environment to build your career. In this role, you will support organizations as they modernize security operations through advanced analytics, cyber data engineering, and AI-enabled capabilities. You will work with leading technologies and help clients strengthen cyber defense while enabling innovation across the enterprise.

Recruiting for this role ends on 12/31/2026.

Work you'll do

As a Cyber SecOps Consultant on the Cyber Defense & Resilience team, you will be responsible for...

  • Supporting the design and modernization of cyber data and analytics programs that improve organizational intelligence and enable scalable delivery models
  • Developing and applying analytics, machine learning, and data science techniques to cyber use cases across security operations, threat detection, and incident response
  • Working with technologies such as Databricks for Cyber, AWS Security Lake, Google SecOps, Splunk, CrowdStrike, and Palo Alto Networks to support cyber data platforms and operational outcomes
  • Assisting with the maintenance, enhancement, governance, and administration of data platforms and applications using standardized, automated, and AI-enabled DataOps capabilities
  • Contributing to AI and analytics initiatives by helping clients experiment, operationalize, and scale solutions using cyber and information technology telemetry data

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 provide clear guidance to others

The team

Cyber Defense & Resilience is an integrated team of security and data technologists working at the intersection of cybersecurity, advanced cyber data engineering, and the use of artificial intelligence and machine learning for cyber defense and operations. The team serves as a trusted advisor and managed service provider, bringing capability and capacity across security data modernization, DataOps, AI, and machine learning to address cyber-specific challenges.

Cyber Detect & Respond practitioners work with clients to modernize large-scale cyber data and analytics programs, support embedded and as-a-service delivery models, and strengthen day-to-day security operations. The team also helps clients harness technologies such as Databricks for Cyber, AWS Security Lake, Google SecOps, Splunk, CrowdStrike, and Palo Alto Networks while advancing AI and analytics capabilities through scalable assets, curated datasets, and operational experience.

Qualifications

Required:

  • 2+ years of analytics consulting or industry experience
  • 2+ years of experience with artificial intelligence development tools, including vector databases such as Pinecone or Elastic, and development frameworks such as LangChain or CrewAI
  • 2+ years of experience in statistical analysis, machine learning, and data mining
  • 2+ years of experience using statistical computer languages such as Python, Structured Query Language (SQL), R, or SAS to prepare data for analysis, perform exploratory analysis, generate features, and support data science workflows
  • 2+ years of experience using cloud-based cybersecurity platforms such as Google SecOps, Amazon Web Services (AWS), or Microsoft Azure
  • 1+ years of experience with security operations center threat hunting and incident response
  • Experience supporting at least one full lifecycle analytics engagement across strategy, design, and implementation
  • Bachelor's degree in Engineering, Mathematics, or Statistics, or 4 years of equivalent professional experience
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • Experience architecting, designing, developing, and deploying enterprise data science solutions that include natural language processing (NLP), chatbots, virtual assistants, computer vision, cognitive services, and big data tools used to manage large datasets
  • Experience applying artificial intelligence (AI), machine learning (ML), and advanced data engineering to cybersecurity use cases, including detection and cyber threat response acceleration
  • Experience parsing and normalizing cybersecurity or information technology telemetry datasets
  • Experience using Python machine learning and deep learning frameworks and libraries, including PyTorch, Keras, TensorFlow, scikit-learn, NumPy, and SciPy
  • Experience designing and implementing Apache open-source frameworks, including Kafka, Storm, and Spark, to support end-to-end data management lifecycle activities
  • Experience managing multiple concurrent task assignments and developing presentation materials using Microsoft Visio and Microsoft PowerPoint

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 $82,600 - $162,800.

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.


Education:Bachelor's DegreeEmployment Type:

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