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Machine Learning Engineer Python Jobs in South Carolina

SynergisticIT

Machine Learning Engineer

Charleston, SC · On-site

Python, Model Training/Testing Primary Responsibilities * Working on the awesome AI product for ... Work with an international top-notch engineering team with full commitment on Machine Learning ...

SARDINE

Machine Learning Engineer

North, SC · Remote

$197K - $270K/yr

Our platform uses device intelligence, behavior biometrics, machine learning, and AI to stop fraud ... What You Bring5+ years in software engineering, with strong backend experience (Go or Python).Hands ...

Indeed

Machine Learning Engineer III

Charleston, SC · On-site

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 ...

Andela

Staff Machine Learning Engineer

North, SC · Remote

We are seeking a Staff Machine Learning Engineer to join our dynamic team specializing in a ... Expert proficiency in Python and experience with frameworks and libraries such as TensorFlow ...

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Machine Learning Engineer Python information

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer Python, and why are they important?

To thrive as a Machine Learning Engineer Python, you need a solid background in computer science, statistics, and mathematics, along with proficiency in Python programming and machine learning concepts. Familiarity with frameworks such as TensorFlow, PyTorch, Scikit-learn, and experience with cloud platforms or MLOps tools are highly valued, as are certifications like Google Professional Machine Learning Engineer. Strong problem-solving abilities, communication skills, and a collaborative mindset help set you apart in this field. These skills enable engineers to design, implement, and deploy effective machine learning solutions that address real-world challenges in dynamic, team-oriented environments.

What are some common challenges faced by Machine Learning Engineers working with Python, and how can they be addressed?

Machine Learning Engineers using Python often encounter challenges such as managing large datasets, ensuring efficient model deployment, and maintaining reproducibility of experiments. Handling data pipelines and model versioning can be complex, especially as projects scale. To address these issues, engineers typically use tools like Pandas and Dask for data handling, Docker for containerization, and MLflow or DVC for tracking experiments and models. Collaborating closely with data engineers, software developers, and product teams is also essential to streamline workflows and ensure models are production-ready.

What is a Machine Learning Engineer Python?

A Machine Learning Engineer Python is a professional who uses the Python programming language to design, build, and deploy machine learning models and systems. They work with large datasets, develop algorithms, and use Python libraries such as TensorFlow, scikit-learn, and PyTorch to solve complex problems. Their responsibilities also include preprocessing data, training models, evaluating performance, and integrating solutions into production environments. Machine Learning Engineers often collaborate with data scientists, software engineers, and business stakeholders to create scalable and efficient machine learning applications.

What is the difference between Machine Learning Engineer Python vs Data Scientist?

AspectMachine Learning Engineer PythonData Scientist
Required CredentialsBachelor's/Master's in CS, Data Science, or related; Python skills; ML certificationsBachelor's/Master's in Statistics, CS, or related; Python/R skills; Data analysis certifications
Work EnvironmentDevelops scalable ML models, deploys algorithms, collaborates with engineering teamsAnalyzes data, builds models, interprets results, communicates insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research institutions

While both roles require Python proficiency and data skills, Machine Learning Engineers focus on building and deploying scalable ML models, whereas Data Scientists analyze data and generate insights. The roles often overlap but differ in their primary focus and responsibilities.

What are popular job titles related to Machine Learning Engineer Python jobs in South Carolina? For Machine Learning Engineer Python jobs in South Carolina, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Python jobs in South Carolina look for? The top searched job categories for Machine Learning Engineer Python jobs in South Carolina are:
What cities in South Carolina are hiring for Machine Learning Engineer Python jobs? Cities in South Carolina with the most Machine Learning Engineer Python job openings:
Machine Learning Engineer Python jobs near you
Machine Learning Engineer III

Machine Learning Engineer III

The Marlin Alliance

Charleston, SC • On-site

Other

This job post has expired today. Applications are no longer accepted.

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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