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Machine Learning Biomedical Engineer Jobs in Saint Augustine, FL

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

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 ...

NGA AI Engineer Manager

Jacksonville, FL · On-site

$73K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

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 21-40

Machine Learning Biomedical Engineer information

See Saint Augustine, FL salary details

$27.5K

$112.3K

$168.8K

How much do machine learning biomedical engineer jobs pay per year?

As of Aug 8, 2026, the average yearly pay for machine learning biomedical engineer in Saint Augustine, FL is $112,321.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,500.00 and $135,200.00 per year, depending on experience, location, and employer.

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

AspectMachine Learning Biomedical EngineerData Scientist in Biomedical Industry
Required CredentialsDegree in Biomedical Engineering, Computer Science, or related fields; knowledge of machine learning and biomedical dataDegree in Data Science, Statistics, or related fields; proficiency in data analysis and machine learning
Work EnvironmentResearch labs, healthcare institutions, biotech companiesHealthcare analytics firms, research institutions, biotech companies
Employer & Industry UsageDevelops algorithms for medical devices, diagnostics, and treatment planningAnalyzes biomedical data to inform clinical decisions, research, and product development

Both roles require expertise in machine learning and biomedical data, but Machine Learning Biomedical Engineers focus on developing algorithms for medical applications, while Data Scientists analyze biomedical data to support research and clinical decisions.

What does a machine learning biomedical engineer do?

A Machine Learning Biomedical Engineer applies machine learning techniques to solve problems in biology and medicine. They develop algorithms and models to analyze complex biomedical data, such as medical images, genetic information, or sensor readings. Their work supports advancements in diagnostics, treatment planning, and personalized medicine. Typically, they collaborate with clinicians, researchers, and other engineers to design systems that improve healthcare outcomes.

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

To thrive as a Machine Learning Biomedical Engineer, you need a strong background in biomedical engineering, data analysis, and machine learning, typically supported by a degree in biomedical engineering, computer science, or a related field. Familiarity with programming languages like Python or R, machine learning frameworks (e.g., TensorFlow, PyTorch), and experience with medical imaging or signal processing tools are commonly required. Critical thinking, problem-solving, and the ability to communicate complex technical concepts to interdisciplinary teams are vital soft skills. These abilities are crucial for developing innovative healthcare solutions, ensuring regulatory compliance, and bridging the gap between technology and medicine.

How does a machine learning biomedical engineer typically collaborate with clinicians and researchers in a healthcare setting?

Machine Learning Biomedical Engineers often work closely with clinicians and researchers to develop algorithms that solve real-world medical challenges. Collaboration usually involves understanding clinical needs, translating them into technical requirements, and iteratively refining models based on feedback from medical experts. Regular meetings, interdisciplinary project teams, and direct participation in data collection or validation studies are common. This collaborative environment ensures that technical solutions are both innovative and clinically relevant, making communication and adaptability essential skills.
What job categories do people searching Machine Learning Biomedical Engineer jobs in Saint Augustine, FL look for? The top searched job categories for Machine Learning Biomedical Engineer jobs in Saint Augustine, FL are:
What cities near Saint Augustine, FL are hiring for Machine Learning Biomedical Engineer jobs? Cities near Saint Augustine, FL with the most Machine Learning Biomedical Engineer job openings:
Infographic showing various Machine Learning Biomedical Engineer job openings in Saint Augustine, FL as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $112,321 per year, or $54 per hour.

Cyber - SecOps - Consultant

Deloitte

Jacksonville, FL

Full-time

Posted 9 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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