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

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 ...

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

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

Launch Vehicle Software Engineer

Cape Canaveral, FL · On-site

$88K - $118K/yr

MANTECH seeks a motivated, customer-oriented Software Engineer to join our team in Cape Canaveral ... Artificial Intelligence, Machine Learning, AI/ML data pipelines, Data Analysis, performance ...

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

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Machine Learning Engineer information

See Melbourne, FL salary details

$29.2K

$119.2K

$179.1K

How much do machine learning engineer jobs pay per year?

As of Jul 13, 2026, the average yearly pay for machine learning engineer in Melbourne, FL is $119,212.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,000.00 and $143,500.00 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.

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 cities near Melbourne, FL are hiring for Machine Learning Engineer jobs? Cities near Melbourne, FL with the most Machine Learning Engineer job openings:
Senior Software Engineer (AI/ML) with Security Clearance

Senior Software Engineer (AI/ML) with Security Clearance

540.co LLC

Patrick Air Force Base, FL • On-site

$114K - $151K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 4 hours ago


Job description

540 is seeking a Senior Software Engineer (AI/ML) to support our partnership with Google and the Department of Defense in advancing mission-critical capabilities for a global data processing platform. This platform leverages Machine Learning, modern cloud and containerized technologies to ingest, process, and analyze high-volume, time-series data. The system leverages cloud-native infrastructure, while incorporating AI/ML capabilities to enhance signal analysis, anomaly detection, and data-driven insights. Engineers on this team build and scale full-stack features across user interfaces, backend services, and data pipelines that power mission-critical analytics. You’ll play a key role in integrating AI/ML-driven capabilities into production systems, enabling faster, more accurate operational decision-making. Location: Patrick SFB, FL or Arlington, VA. Candidates should be local to either location. Onsite support may be required based on mission and customer needs. Travel up to 25%.
Citizenship & Clearance Requirement: Per client requirements, candidates must be U.S. Citizens with an active DoD clearance with TS/SCI eligibility
Education Requirement: Bachelor's Degree in Computer Science or related field (preferred)
540 Internal Thrive Level: Senior Software Engineer WHY 540? 540 is a forward-thinking company that the government turns to in order to #getshitdone. We don’t just talk about innovation – we deliver it. We break down barriers, build impactful technology, and solve mission-critical problems. HOW YOU’LL DRIVE IMPACT Design and develop machine learning models and applications for deployment to cloud-native services
Collaborate with data engineers and data scientists to productionize machine learning models and data pipelines
Collaborate with a cross-functional team of architects, engineers, and scientists to design and deploy Machine Learning Operations (MLOps) at scale Integrate AI/ML capabilities into production systems (e.g., model inference APIs, decision-support features, anomaly detection workflows)
Design and optimize data models and persistence layers to support both transactional and analytical workloads
Enable intelligent application behavior by delivering AI and ML features to user-facing applications
Contribute to technical design documentation and system architecture artifacts
Lead or participate in code reviews, testing, and troubleshooting to ensure high-quality software
Drive system reliability through robust testing
Improve system performance, scalability, and reliability as the platform evolves REQUIRED SKILLS & EXPERIENCE 8+ years of professional software development experience
Experience developing microservices in containerized environments
Experience with, or a strong conceptual understanding of, LLM-based applications, RAG pipelines, and AI-driven decision systems
Experience with Python
Experience working with relational databases and data warehouses
Experience integrating AI/ML capabilities into applications (e.g., working with model inference APIs, ML pipelines, or data-driven features)
Ability to produce technical design documentation (system diagrams, architecture artifacts)
Familiarity with MLOps concepts (model deployment, monitoring, versioning)
Ability to design with future scalability and platform evolution in mind Demonstrated ownership and ability to drive work from concept to production
Strong problem-solving skills and ability to navigate ambiguity
Excellent communication skills, including working directly with stakeholders or clients NICE TO HAVE Experience with Google Cloud Platform (GCP) or similar cloud environments
Experience designing and consuming RESTful APIs
Experience with API gateways and API management platforms, such as Google Apigee
Familiarity with API authentication and authorization (PKI, OAuth2, JWT, LDAP, SAML, etc.)
Experience working on U.S. Federal Government programs, particularly DoD environments
Google Cloud Professional-level certifications BENEFITS & PERKS Flexible PTO + all Federal holidays off
Health, dental and vision insurance plans
Flexible Spending Account (FSA)
401k with employer match
Company-sponsored life insurance, short- and long-term disability Professional development (training, certifications, conferences)
Paid cloud developer accounts
Referral bonuses
HQ office perks (parking / metro reimbursement, nitro coffee & lunches) Annual social events (540 Week, hackathon, charity golf tournament, etc.)
Access to 540’s Washington Capitals & Nationals tickets EQUAL EMPLOYMENT OPPORTUNITY (EEO) 540's policy is to provide equal employment opportunity to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.