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Phd Machine Learning Jobs in Florida (NOW HIRING)

ENSCO, Inc.

Machine Learning Engineer

Melbourne, FL · On-site

Masters or PhD degree in Machine Learning, Data Science, or Mathematics, or equivalent. Experience with ML/DL algorithms extracting signal from noise. Past experience being able to develop solutions ...

ENSCO, Inc.

Machine Learning Engineer

Melbourne, FL · On-site

$73K - $131K/yr

S. Citizen Qualifications Desired: • Masters or PhD degree in Machine Learning, Data Science, or Mathematics, or equivalent. • Experience with ML/DL algorithms extracting signal from noise. • ...

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Phd Machine Learning information

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How much do phd machine learning jobs pay per hour?

As of Jul 14, 2026, the average hourly pay for phd machine learning 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 PhD in Machine Learning?

A PhD in Machine Learning is an advanced doctoral degree focused on developing new algorithms, theories, and applications in the field of machine learning. Graduates typically conduct original research, contribute to academic publications, and often specialize in areas like deep learning, reinforcement learning, or probabilistic modeling. This degree prepares individuals for careers in academia, industry research labs, or leadership roles in tech companies. The program usually involves coursework, comprehensive exams, and the completion of a dissertation based on novel research.

What are the key skills and qualifications needed to thrive as a PhD-level Machine Learning professional, and why are they important?

To thrive as a PhD-level Machine Learning professional, you need deep expertise in mathematics, statistics, computer science, and advanced machine learning algorithms, typically supported by a doctoral degree. Proficiency with programming languages like Python or R, machine learning frameworks such as TensorFlow or PyTorch, and experience with large-scale data systems are essential. Strong problem-solving skills, critical thinking, and effective communication set outstanding candidates apart by enabling them to tackle complex research challenges and collaborate across teams. These skills and qualities are crucial for driving innovation, publishing research, and developing impactful machine learning solutions.

What are some common challenges faced by PhD-level professionals in machine learning when transitioning from academia to industry roles?

PhD graduates in machine learning often encounter challenges such as adapting to faster-paced project timelines, aligning research with business objectives, and collaborating in multidisciplinary teams. Unlike academia, where projects can be exploratory and long-term, industry roles usually require actionable results within shorter deadlines. Additionally, communicating complex technical ideas to non-technical stakeholders and prioritizing practical solutions over theoretical novelty are key adjustments. However, these challenges also present opportunities for professional growth and broader impact.

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

AspectPhd Machine LearningData Scientist
Required CredentialsPhD in Computer Science, AI, or related fieldBachelor's or Master's in Data Science, Statistics, or related field
Work EnvironmentResearch labs, academia, R&D departmentsBusiness, tech companies, analytics teams
Industry UsageResearch-focused roles, advanced algorithm developmentData analysis, model building, business insights
Common Search/ComparisonYesYes

While both roles involve working with data and algorithms, a Phd Machine Learning typically focuses on research, developing new models, and theoretical work, often in academic or R&D settings. A Data Scientist applies these techniques to solve practical business problems, analyze data, and generate insights in industry environments.

What cities in Florida are hiring for Phd Machine Learning jobs? Cities in Florida with the most Phd Machine Learning job openings:
Phd Machine Learning jobs near you
Infographic showing various Phd Machine Learning job openings in Florida as of July 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 2% Temporary, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $35,472 per year, or $17.1 per hour.
Machine Learning Engineer

Machine Learning Engineer

ENSCO, Inc.

Melbourne, FL • On-site

Other

Re-posted 23 days ago

Job description

ENSCO, Inc. is seeking a Machine Learning Engineer with direct experience and applications with using Machine Learning (ML) and Deep Learning (DL) models, frameworks, architectures, pipelines, and advanced data analytics, to address difficult problem sets.  Work closely with other senior scientist to understand problem sets, physical data feature sets and parameters.  The successful candidate must have demonstrated understanding of signal processing, data fusion, feature extraction, and be able to apply it towards ML and DL solutions.  Assess algorithm performance of features by building datasets and designing and executing well-controlled experiments.
ENSCO's Mission Systems Group (MSG) provides innovative customized products and services vital to national safety and security.  A primary focus area is the development of advanced algorithm development and integration for multipurpose data sets.
 

Qualifications Required:
        Bachelors degree in Machine Learning, Data Science, Mathematics, or equivalent in a related discipline.  Direct relevant military experience will also be considered.
        Minimum of 3 years related industry experience in machine learning, data science, and analytics.
        Proven track record of successful data science and algorithm implementation.
        Provide mentorship to junior ML engineers.
        A self-starter with excellent oral and written communication skills.
        Experience navigating and programming within the Linux environment.
        Experience working with structured and unstructured databases.
        Advanced proficiency with data science languages (e.g. Python, Matlab,)
        Demonstrated experience with Deep Learning frameworks (e.g. PyTorch, TensorFlow/Keras, scikit-learn, MXNet).
        Experience working with large data sets and ability to extract relevant information from data sets.
         The ability to obtain and maintain a US security clearance is required for this position, for which you must be a U.S. Citizen

Qualifications Desired:
        Masters or PhD degree in Machine Learning, Data Science, or Mathematics, or equivalent.
        Experience with ML/DL algorithms extracting signal from noise.
        Past experience being able to develop solutions using disparate data sets through ML techniques.
        DevOps experience involving CI/CD pipelines to build and deploy.
        Experience working with container orchestration technologies (e.g. Docker/Kubernetes).
        An Active TS/SCI clearance.
 

Work Location Type: Hybrid
Required Certifications: None
U.S. Citizenship Required: Yes
Security Clearance Required: Ability to obtain
Employment Type: Regular Full-time
Background Check Type:  7 Year Pre-Employment
Drug Screen Required: None
Position Contingent Upon Contract Award: Yes

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