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Remote Machine Learning Jobs in South Carolina (NOW HIRING)

Lead Engineer, AI Attack Simulation

Charleston, SC ยท On-site +1

$95K - $126K/yr

Experience with AI red teaming, adversarial machine learning, AI security evaluation, or autonomous ... Fully Remote: We are a completely remote global team. Though we're distributed, we are intentional ...

New

Senior AI Product Manager

Charleston, SC ยท On-site +1

$118K - $156K/yr

... of machine learning and artificial intelligence capabilities within Workiva's platform. In this ... Reliable internet connection required during remote work periods How You'll Be Rewarded Salary ...

$99K - $225K/yr

... IoT, machine learning, and artificial intelligence. In an increasingly connected world, massive ... Remote : If this position is listed as remote, there may still be occasions when you are required ...

$143K - $187K/yr

Lead projects using regression and statistical analysis, machine learning, time series forecasting, and data visualization. Work Schedule: Monday - Friday, 8:00am - 4:30pm Compressed/Flexible: May be ...

New

Coordinate with subconsultants and remote team members to compose proposal text with a consistent ... copy machines. May occasionally be exposed to noise. * While performing the duties of this job ...

Coordinate with subconsultants and remote team members to compose proposal text with a consistent ... copy machines. May occasionally be exposed to noise. * While performing the duties of this job ...

Sr. Software Engineer - Platform

North, SC ยท Remote

$189K - $231K/yr

Location This is a remote role based in North America, with a strong preference for candidates located in the U.S. Eastern Time Zone . The Opportunity Enterprises are moving AI agents from ...

Showing results 41-60

Remote Machine Learning information

See South Carolina salary details

$23.7K

$39.5K

$81.7K

How much do remote machine learning jobs pay per year?

As of Aug 9, 2026, the average yearly pay for remote machine learning in South Carolina is $39,516.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,200.00 and $42,700.00 per year, depending on experience, location, and employer.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

What are some effective strategies for collaborating with team members while working remotely as a machine learning engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

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

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

Can remote machine learning engineers work remotely?

Yes, remote machine learning engineers can work remotely, as many companies offer flexible work arrangements for data science and AI roles. These positions typically require strong programming skills, experience with tools like Python and TensorFlow, and the ability to collaborate virtually using communication platforms. Remote work in this field is common, especially for roles focused on model development, data analysis, and deployment.
What are the most commonly searched types of Machine Learning jobs in South Carolina? The most popular types of Machine Learning jobs in South Carolina are:
What cities in South Carolina are hiring for Remote Machine Learning jobs? Cities in South Carolina with the most Remote Machine Learning job openings:
Infographic showing various Remote Machine Learning job openings in South Carolina as of August 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 100% Remote job distribution, with an average salary of $39,516 per year, or $19 per hour.

Senior AI Solutions Architect (Remote Opportunity)

VetsEZ

Charleston, SC โ€ข On-site, Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 17 days ago


Job description

VetsEZ is seeking a Senior AI Solutions Architect to lead the design and implementation of enterprise Artificial Intelligence (AI) solutions supporting the Department of Veterans Affairs (VA), with responsibility for AI architecture across the JLV contract. The initial assignment will support the Joint Longitudinal Viewer (JLV) AI Search and Summarization initiative, delivering a secure, governed AI-assisted search and summarization MVP for development, clinical evaluation, and designated-user testing in an approved lower environment utilizing Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) within a secure AWS cloud environment.
Working closely with Government stakeholders, clinical subject matter experts, software engineers, cybersecurity teams, and DevSecOps personnel, this individual will establish the overall AI solution architecture while ensuring scalability, security, interoperability, Responsible AI, and compliance with Federal cybersecurity and AI governance requirements.
Responsibilities:
  • Lead the architecture, design, and implementation of enterprise AI solutions utilizing Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG).
  • Design scalable, secure, and maintainable AI architectures supporting enterprise healthcare applications.
  • Define solution architecture, data flows, system interfaces, AI orchestration, and integration patterns.
  • Evaluate AI technologies, services, and frameworks to support current and future project needs.
  • Ensure architecture supports approved future phases without expanding the authorized MVP scope.
  • Design AI solutions leveraging Amazon Bedrock and AWS cloud services.
  • Architect secure AI pipelines supporting approved document access and processing, retrieval, vector search, prompt orchestration, and AI-assisted summarization.
  • Define strategies for model selection, prompt management, retrieval optimization, and AI performance tuning.
  • Define monitoring and evaluation strategies to detect model, prompt, retrieval, and data drift and address degradation in accuracy, safety, or clinical relevance.
  • Optimize AI architectures for scalability, operational cost, reliability, and response time.
  • Collaborate with DevSecOps teams to support deployment automation and operational readiness.
  • Design integration between AI services and existing enterprise healthcare applications.
  • Define secure interfaces utilizing REST APIs and modern integration patterns.
  • Ensure solutions align with healthcare interoperability standards including FHIR, HL7, and CCD.
  • Collaborate with application development teams to integrate AI capabilities into clinician workflows.
  • Promote consistent architecture patterns and engineering best practices across JLV development teams.
  • Design AI solutions that comply with Federal cybersecurity, privacy, and Responsible AI requirements.
  • Incorporate Human-in-the-Loop (HITL), source traceability, approved data boundaries, retention and purge controls, explainability, auditability, and governance principles into solution architecture.
  • Support Authority to Operate (ATO), AI governance, Security Impact Analysis (SIA), and technology approval activities.
  • Ensure secure handling of Protected Health Information (PHI) and Personally Identifiable Information (PII).
  • Collaborate with cybersecurity teams to implement secure AI architectures and operational controls.
  • Serve as the technical leader for AI architecture across the JLV contract.
  • Mentor software engineers and provide architectural guidance throughout the software development lifecycle.
  • Participate in architecture reviews, design sessions, sprint planning, backlog refinement, and technical estimation.
  • Produce architecture documentation, system design artifacts, interface specifications, and implementation guidance.
  • Present technical approaches and architectural recommendations to Government leadership and stakeholders.

Requirements:
  • Bachelor's degree in Computer Science, Software Engineering, Information Systems, Artificial Intelligence, Data Science, or a related technical field, or equivalent experience.
  • 10+ years designing enterprise software solutions.
  • 5+ years designing cloud-native architectures utilizing AWS or comparable cloud platforms.
  • Demonstrated experience architecting Artificial Intelligence, Machine Learning, or Generative AI solutions.
  • Experience implementing enterprise applications utilizing Amazon Bedrock or similar AI platforms.
  • Experience leading technical architecture across multidisciplinary engineering teams.
  • Amazon Bedrock and AWS cloud services
  • Large Language Models (LLMs)
  • Retrieval-Augmented Generation (RAG)
  • Prompt engineering, source-grounded AI evaluation, and hallucination testing
  • Vector databases, embeddings, and semantic search
  • REST APIs and enterprise integration
  • Cloud architecture and distributed systems
  • DevSecOps and CI/CD
  • Healthcare interoperability (FHIR, HL7, CCD)

Additional Qualifications:
  • Strong understanding of enterprise architecture principles and cloud-native application design.
  • Experience balancing AI performance, scalability, security, explainability, and operational cost.
  • Excellent analytical, architectural, and problem-solving skills.
  • Strong written and verbal communication skills with the ability to communicate complex technical concepts to diverse audiences.
  • Ability to obtain and maintain a Government Public Trust clearance.
  • Experience supporting the Department of Veterans Affairs (VA), Department of Defense (DoD), or other Federal healthcare organizations.
  • Experience designing AI-enabled clinical workflow, search, summarization, or clinician-support solutions requiring human validation.
  • Knowledge of Responsible AI, NIST AI Risk Management Framework (AI RMF), NIST SP 800-53, FISMA, and FedRAMP, including applicable High-Impact AI requirements.
  • Familiarity with clinical terminology standards including SNOMED CT, ICD-10, RxNorm, and LOINC.
  • AWS Solutions Architect, AWS AI, Machine Learning, or other AWS cloud certifications are highly desirable.

Benefits:
  • Medical, Dental, and Vision Insurance
  • 401(k) with Employer Match
  • Paid Time Off plus Federal Holidays
  • Corporate Laptop
  • Professional Development and Training Opportunities
  • Remote Opportunity

Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, or protected veteran status.
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