ZipRecruiter

Log In

1

Machine Learning Engineer Jobs in Melbourne, FL (NOW HIRING)

ENSCO, Inc.

Machine Learning Engineer

Melbourne, FL

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 ...

Bespoke Labs

Machine Learning Engineer

Melbourne, FL · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

540

Senior Software Engineer (AI/ML)

Satellite Beach, FL

$113K - $149K/yr

This platform leverages Machine Learning, modern cloud and containerized technologies to ingest ... Engineers on this team build and scale full-stack features across user interfaces, backend services ...

540

Security Operations Engineer

Satellite Beach, FL

This platform leverages Machine Learning, modern cloud and containerized technologies to ingest ... You will work closely with engineers, architects, and security stakeholders to ensure systems are ...

kgs

Data Scientist

Cape Canaveral, FL

Python, R, or similar programming languages * Machine learning frameworks (scikit-learn, TensorFlow, PyTorch) * Statistical analysis and modeling * Data visualization tools (Matplotlib, Seaborn ...

kgs

Data Scientist

Cape Canaveral, FL

Python, R, or similar programming languages * Machine learning frameworks (scikit-learn, TensorFlow, PyTorch) * Statistical analysis and modeling * Data visualization tools (Matplotlib, Seaborn ...

next page

Showing results 1-20

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Melbourne, FL

Machine Learning Engineer information

See Melbourne, FL salary details

$29.2K

$119.4K

$179.4K

How much do machine learning engineer jobs pay per year?

As of Jul 30, 2026, the average yearly pay for machine learning engineer in Melbourne, FL is $119,359.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,100.00 and $143,700.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

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.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

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 engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

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.

More about Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Melbourne, FL? The most popular types of Machine Learning Engineer jobs in Melbourne, FL are:
What are popular job titles related to Machine Learning Engineer jobs in Melbourne, FL? For Machine Learning Engineer jobs in Melbourne, FL, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Melbourne, FL look for? The top searched job categories for Machine Learning Engineer jobs in Melbourne, FL are:
What cities near Melbourne, FL are hiring for Machine Learning Engineer jobs? Cities near Melbourne, FL with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Melbourne, FL as of July 2026, with employment types broken down into 50% Full Time, and 50% Nights. Highlights an 100% In-person job distribution, with an average salary of $119,359 per year, or $57.4 per hour.

Machine Learning Engineer

ENSCO, Inc.

Melbourne, FL

Other

Re-posted 8 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

Apply