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Remote Machine Learning Compiler Engineer Jobs in Johns Island, SC

Senior AI Product Manager

Charleston, SC · On-site +1

$118K - $156K/yr

... of machine learning and artificial intelligence capabilities within Workiva's platform. In this ... You will collaborate directly with engineering, data science, and design teams to deliver high ...

... data science, engineering, and advanced mathematics. * Conceptual Teaching & Problem-Solving ... machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive Instruction:

... data science, engineering, and advanced mathematics. * Conceptual Teaching & Problem-Solving ... machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive Instruction:

Geospatial Analyst

Charleston, SC · On-site +1

$55K - $72K/yr

Master's degree with two plus years of related experience in geography, remote sensing, GIS, or ... Knowledge or experience related to land cover classification using machine learning or more ...

Master's degree with two plus years of related experience in geography, remote sensing, GIS, or ... Knowledge or experience related to land cover classification using machine learning or more ...

Geospatial Analyst

Charleston, SC · On-site +1

$55K - $72K/yr

Master's degree with two plus years of related experience in geography, remote sensing, GIS, or ... Knowledge or experience related to land cover classification using machine learning or more ...

Experience in multiple programming languages, including R and Python. * Deep understanding of GLMs and GBMs. * Familiarity with AI and machine learning concepts, including supervised and unsupervised ...

Statics Tutor

Mount Pleasant, SC · Remote

$18 - $40/hr

... machine design, and construction engineering. * Curriculum Awareness & Adaptive Instruction ... Ability to adapt to different learning styles and student needs. Ways To Connect With Students * 1 ...

Statics Tutor

Charleston, SC · Remote

$18 - $40/hr

... machine design, and construction engineering. * Curriculum Awareness & Adaptive Instruction ... Ability to adapt to different learning styles and student needs. Ways To Connect With Students * 1 ...

... machine dynamics, and advanced engineering coursework. * Conceptual Teaching & Problem-Solving ... Ability to adapt to different learning styles and student needs. Ways To Connect With Students * 1 ...

Showing results 21-40

Remote Machine Learning Compiler Engineer information

See Johns Island, SC salary details

$72.2K

$161.2K

$197.4K

How much do remote machine learning compiler engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for remote machine learning compiler engineer in Johns Island, SC is $161,216.00, according to ZipRecruiter salary data. Most workers in this role earn between $137,700.00 and $197,400.00 per year, depending on experience, location, and employer.

What is a remote machine learning compiler engineer?

A Remote Machine Learning Compiler Engineer is a software engineer who specializes in developing and optimizing compilers specifically for machine learning workloads, while working from a remote location. Their primary responsibilities include designing and implementing compiler features that translate machine learning models into efficient code for various hardware platforms, such as CPUs, GPUs, or specialized accelerators. They collaborate closely with machine learning researchers, hardware engineers, and software developers to ensure high performance and compatibility. In addition to strong programming skills, they typically require expertise in compiler theory, machine learning frameworks, and hardware architectures. This role allows for flexible, location-independent work while contributing to cutting-edge AI technologies.

How does a remote machine learning compiler engineer typically collaborate with cross-functional teams to optimize model deployment?

As a Remote Machine Learning Compiler Engineer, you will frequently collaborate with data scientists, hardware engineers, and software developers to ensure that machine learning models are efficiently compiled and deployed on target platforms. Communication often takes place through virtual meetings, code reviews, and shared documentation tools. You'll be responsible for translating research models into optimized code, troubleshooting performance bottlenecks, and integrating feedback from various stakeholders. Effective teamwork is crucial, as the success of deployments often depends on iterative feedback and close alignment with both the ML research and hardware teams.

What are the key skills and qualifications needed to thrive as a remote machine learning compiler engineer, and why are they important?

To thrive as a Remote Machine Learning Compiler Engineer, you need a strong background in computer science, proficiency in programming languages like C++ and Python, and expertise in compiler theory and machine learning frameworks. Familiarity with ML compilers such as TVM or XLA, and experience using version control and CI/CD systems are commonly required, along with a relevant bachelor's or master's degree. Outstanding problem-solving, collaboration, and communication skills are essential for working effectively in distributed teams and across technical domains. These skills and qualities enable the development of efficient, scalable ML solutions that bridge software and hardware, ensuring high performance and innovation.

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

AspectRemote Machine Learning Compiler EngineerRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Software Engineering, or related fields; knowledge of compiler design and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in programming, statistics, and data analysis
Work EnvironmentPrimarily software development, compiler optimization, and ML model deploymentData analysis, model building, and interpretation of results
Industry UsageTech companies, AI startups, hardware firms focusing on ML hardware accelerationTech, finance, healthcare, and research organizations

While both roles involve working with machine learning, the Remote Machine Learning Compiler Engineer focuses on developing and optimizing compilers for ML models, whereas the Remote Data Scientist concentrates on analyzing data and building predictive models. The roles share some technical skills but differ in their core responsibilities and work environments.

What cities near Johns Island, SC are hiring for Remote Machine Learning Compiler Engineer jobs?

Cities near Johns Island, SC with the most Remote Machine Learning Compiler Engineer job openings:

Senior AI Solutions Architect (Remote Opportunity)

VetsEZ

Charleston, SC • On-site, Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted yesterday


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.

Security Clearance Requirements

  • U.S. Citizenship is required.
  • All selected candidates must successfully complete a background check.
  • Ability to obtain and maintain a Government/Public Trust clearance, including required fingerprinting, when required for the position.

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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Employment Type: FULL_TIME