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Machine Learning Engineer Jobs in Charleston, SC

Indeed

Machine Learning Engineer III

Charleston, SC

Comscore, Total Visits, March 2025) Day to Day As a Machine Learning Engineer III, you will be a team lead. You will own one of the team's major workstreams, help drive technical direction for the ...

Indeed

Senior Machine Learning Engineer

Charleston, SC

$97K - $134K/yr

Comscore, Total Visits, March 2025) Day to Day As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be ...

New

Varsity Tutors

Machine Learning Tutor

Mount Pleasant, SC · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Charleston, SC · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Navstar

AI Ops - Data Engineer III

Charleston, SC · On-site

$300K/yr

Bachelor of Science in Computer Science, Data Science, Geography, Math, Machine Learning, or Statistics. * Strong, hands-on programming skills in Python, Go (Golang), Rust, Pandas, R, SQL, or related ...

Epic

Software Engineer

Charleston, SC · On-site

... and machine learning tools to drive innovation in healthcare. • Invent better ways to reduce ... Engineering, Computer Engineering, or a related field • A history of academic excellence or ...

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Showing results 1-20

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Charleston, SC

Machine Learning Engineer information

See Charleston, SC salary details

$29.5K

$120.5K

$181.1K

How much do machine learning engineer jobs pay per year?

As of Jun 9, 2026, the average yearly pay for machine learning engineer in Charleston, SC is $120,504.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,000.00 and $145,100.00 per year, depending on experience, location, and employer.

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.

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 jobs make $3,000 a month without a degree?

A Machine Learning Engineer typically requires a degree, but roles such as data annotator, technical support specialist, or freelance programmer can sometimes earn around $3,000 monthly without a formal degree, especially with relevant skills and experience. These jobs often involve self-taught skills, online certifications, or on-the-job training and may require proficiency in tools like Python or cloud platforms.
More about Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Charleston, SC? The most popular types of Machine Learning Engineer jobs in Charleston, SC are:
What are popular job titles related to Machine Learning Engineer jobs in Charleston, SC? For Machine Learning Engineer jobs in Charleston, SC, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Charleston, SC look for? The top searched job categories for Machine Learning Engineer jobs in Charleston, SC are:
What cities near Charleston, SC are hiring for Machine Learning Engineer jobs? Cities near Charleston, SC with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Charleston, SC as of June 2026, with employment types broken down into 98% Full Time, and 2% Part Time. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $120,504 per year, or $57.9 per hour.
Machine Learning Engineer III

Machine Learning Engineer III

The Marlin Alliance

Charleston, SC • On-site

Other

Posted 26 days ago

Job description

Machine Learning Engineer III

The Marlin Alliance, Inc. | San Diego, CA | Hybrid | Clearance Required

Incorporated in 2002, The Marlin Alliance is a digital transformation company dedicated to ensuring our clients compete and win in tomorrow's digital world. We specialize in creating technical solutions that allow for seamless execution of automated business processes and the generation of governed, machine-consumable data. From strategic planning to advanced analytics and cybersecurity, our team provides cutting-edge, cross-disciplinary solutions. We are seeking motivated professionals who share our agile, solution-oriented mindset and are ready to deliver the real, practical results relied upon by our clients.

Position Overview

The Machine Learning Engineer III designs and implements sophisticated models and algorithms tailored for naval applications, leveraging expertise in modern machine learning methods and cloud-native development. This technical lead oversees the full lifecycle of AI solutions, from initial architectural design to deployment within distributed systems and operational Navy environments. By collaborating across multidisciplinary teams and applying rigorous software engineering standards, the role ensures the delivery of scalable, mission-critical intelligence that meets complex maritime requirements.

Location:

San Diego, CA

On site NAVWAR

There will be some (15%) travel required to Arlington, VA; Colorado Springs, CO; Charleston, SC; Denver, CO; or other customer locations as needed.

Citizenship and Clearance Requirements:

US Citizenship is required

No Dual Citizenship

Active Secret clearance required; TS SCI clearance highly preferred

Responsibilities:
  • Design, develop, and implement machine learning models and algorithms for naval applications.
  • Develop and deploy algorithms, mathematical models, and machine learning models into real-world operational environments.
  • Perform data preprocessing, feature engineering, model evaluation, and validation.
  • Collaborate with engineers, data scientists, and mission stakeholders to align ML solutions with operational requirements.
  • Develop cloud-native ML pipelines using AWS, Azure, Docker, Kubernetes, or equivalent platforms.
  • Implement ML solutions using frameworks such as TensorFlow, PyTorch, and scikit-learn.
  • Contribute to distributed computing and parallel processing approaches to optimize ML model performance.
  • Participate in CI/CD pipeline development, automation, and DevSecOps workflows.
  • Apply cybersecurity principles in the design and deployment of machine learning systems.
  • Provide documentation, technical reports, and engineering artifacts consistent with PMAT and government standards.
  • Stay current with advancements in machine learning, data science, and emerging technologies relevant to naval and DoD applications.
Required Skills and Experience:
  • 10+ years of experience as a data scientist, data engineer, geospatial engineer, machine learning engineer, or software engineer.
  • Proven experience developing and deploying algorithms, mathematical models, or machine learning models in real-world applications.
  • Strong programming skills in Python.
  • Familiarity with cloud platforms (e.g., AWS, Azure) or containerization technologies (e.g., Docker, Kubernetes).
  • Familiarity with software engineering best practices, including Git.
  • Experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
  • Strong programming skills in Java, C++, Go, or Rust.
  • Experience with distributed computing and parallel processing.
  • Experience with CI/CD pipelines and automation tools (GitHub Actions, GitLab CI, Jenkins).
  • Strong analytical, problem-solving, and communication skills.
  • Ability to work effectively in a collaborative team environment.
  • Previous experience supporting government agencies or military organizations.
  • Ability to safely carry tools, equipment, and materials aboard ship, including ascending and descending shipboard ladders (stairwells) and navigating confined spaces while maintaining required points of contact. Tools and equipment will weigh no more than 50 lbs.
  • Ability to perform required work aboard Navy vessels and in shipboard environments, including navigating narrow passageways, ascending, and descending ladders (stairwells), working on elevated platforms, and operating in variable sea conditions.
  • Ability to perform activities on a reoccurring basis during shipboard operations or testing evolutions.
  • Ability to comply with Navy safety requirements and wear required personal protective equipment (PPE).
Preferred Skills and Experience:
  • Experience with cloud-native architecture and software API design.
  • Experience integrating machine learning into operational DoD systems or edge computing environments.
  • Familiarity with DoD AI strategies, MLOps, or data engineering in secure environments.
  • Experience supporting NAVWAR, NIWC Pacific, or other Navy C2/ISR programs.
Education and Certification Requirements:
  • Bachelor of Science degree in Artificial Intelligence, Data Science, Computer Science, Machine Learning, or Statistics.
  • Advanced degrees (MS/PhD) in related fields are preferred but not required.
  • Additional certifications in cloud, cybersecurity, AI/ML, or DevSecOps are a plus if required by contract.
Work Environment and Mental/Physical Demands:

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this position. Reasonable accommodations may be made to enable individuals with disabilities to perform the functions.

  • Typical office environment with no unusual hazards.
  • The noise level in the work environment is usually moderate.
  • Constant sitting while using the computer terminal.
  • Constant use of sight abilities while reviewing documents.
  • Constant use of speech/hearing abilities for communication.
  • Occasional reaching, stooping, kneeling, or crouching may be required.
  • Occasional lifting up to 20 pounds.
  • Constant use of mental alertness.
  • Frequent work under deadlines.
Compensation

$140,000 – $195,000 annually, commensurate with experience.

Work Environment

Typical professional office environment. Requires sustained focus, extended periods at a computer workstation, and occasional lifting up to 20 lbs. Reasonable accommodations will be made for individuals with disabilities.

An Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities.

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