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Remote Machine Learning Compiler Engineer Jobs in Ohio

ERP Suites

AI & Mobile Product Manager

Loveland, OH · On-site +1

... machine learning, AI agents, automation, model governance, and responsible AI practices. Daily Activities: • Collaborate with engineering, data science, and design teams to review progress and ...

micro1 AI

Engineering AI Evaluator (PhD)

Columbus, OH · Remote

$80 - $90/hr

PhD Engineer (Electrical, Mechanical, Chemical) Role Type: Contractor Location: Remote micro1 is ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

Cushman & Wakefield

Applied AI Engineer

Cincinnati, OH · On-site +1

Success requires equal fluency in modern AI tooling (including machine learning, NLP, and ... The Applied AI Engineer embeds directly with operational leaders to translate real-world business ...

Cushman & Wakefield

Applied AI Engineer

Cincinnati, OH · On-site +1

Success requires equal fluency in modern AI tooling (including machine learning, NLP, and ... The Applied AI Engineer embeds directly with operational leaders to translate real-world business ...

Cushman & Wakefield

Applied AI Engineer

Cincinnati, OH · On-site +1

Success requires equal fluency in modern AI tooling (including machine learning, NLP, and ... The Applied AI Engineer embeds directly with operational leaders to translate real-world business ...

Cushman & Wakefield

Applied AI Engineer

Cincinnati, OH · On-site +1

Success requires equal fluency in modern AI tooling (including machine learning, NLP, and ... The Applied AI Engineer embeds directly with operational leaders to translate real-world business ...

Premier Health

SENIOR DATA ARCHITECT - DIGITAL HEALTH

Dayton, OH · On-site +1

$65.25 - $87.50/hr

... programming (Python/Scala) * Experience with Azure ecosystem, preferable * Knowledge of Linux OS * Familiarity with machine learning and data science concepts Benefits * Fully Remote work-from-home ...

Huntington

Senior Data Scientist - AI

Columbus, OH · On-site +1

Conducts research on cutting-edge techniques and tools in machine learning/deep learning/artificial ... Remote roles will also have the opportunity to come together in our offices for moments that matter.

Huntington

Senior Data Scientist - AI

Columbus, OH · On-site +1

Conducts research on cutting-edge techniques and tools in machine learning/deep learning/artificial ... Remote roles will also have the opportunity to come together in our offices for moments that matter.

Huntington

Senior Data Scientist - AI

Columbus, OH · On-site +1

Conducts research on cutting-edge techniques and tools in machine learning/deep learning/artificial ... Remote roles will also have the opportunity to come together in our offices for moments that matter.

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All JobsMachine Learning Compiler Engineer JobsRemote Machine Learning Compiler Engineer JobsRemote Machine Learning Compiler Engineer Jobs in Ohio

Remote Machine Learning Compiler Engineer information

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 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.

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 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 are the most commonly searched types of Machine Learning Compiler Engineer jobs in Ohio? The most popular types of Machine Learning Compiler Engineer jobs in Ohio are:
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What job categories do people searching Remote Machine Learning Compiler Engineer jobs in Ohio look for? The top searched job categories for Remote Machine Learning Compiler Engineer jobs in Ohio are:
What cities in Ohio are hiring for Remote Machine Learning Compiler Engineer jobs? Cities in Ohio with the most Remote Machine Learning Compiler Engineer job openings:
Remote Machine Learning Compiler Engineer jobs near you
AI/ML Engineer

AI/ML Engineer

Frontier Technology Inc.

Dayton, OH • Remote

Full-time

Re-posted 25 days ago

Job description

FTI Defense is seeking a hands-on AI/ML Engineer to design, build, and deploy advanced machine learning solutions supporting defense and national security missions. This role focuses on execution in oversight, ideal for an engineer who thrives in the code, enjoys building end-to-end pipelines, and takes pride in seeing their work directly impact operational systems.

FTI Defense delivers mission-focused solutions to the Department of Defense/Depratment of War (DoD/DoW) and Intelligence Community (IC) through advanced engineering, digital transformation, and program execution expertise. We help our customers solve complex challenges and achieve mission success by integrating people, process, and technology.


  • Design, develop, and deploy AI/ML models and pipelines that meet mission and performance objectives.
  • Build, train, and fine-tune models using frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, and LangChain.
  • Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference orchestration).
  • Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval architectures (RAG, graph, hybrid).
  • Write clean, efficient Python code for data ingestion, feature engineering, embeddings, and inference services.
  • Experiment with fine-tuning and optimization of LLMs and task-specific models (LoRA, QLoRA, PEFT).
  • Contribute to agent-based applications using frameworks like LangGraph, AutoGen, CrewAI, or DSPy.
  • Integrate AI services into real-world systems via APIs, event-driven workflows, or UI copilots.
  • Collaborate with data engineers, software developers, and mission analysts to ensure AI models are production-ready and aligned with customer needs.
  • Participate in peer reviews, contribute to shared repositories, and document models and experiments for reproducibility.

Minimum Requirements:

  • Must be a U.S. citizen and be willing to obtain and maintain a security clearance, as needed.
  • 6-10+ years of professional experience developing and deploying AI/ML solutions in production environments.
  • Minimum of 3 years' professional experience within the Department of Defense/Department of War (DoD/DoW) AI assurance, security, and deployment environments.
  • Strong Python development skills with hands-on experience building AI/ML solutions.
  • Direct experience with ML frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, or LangChain.
  • Proven ability to build and deploy MLOps pipelines using MLflow, Kubeflow, DVC, or equivalent.
  • Working knowledge of vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval-based architectures (RAG, hybrid, graph).
  • Professional experience fine-tuning and evaluating LLMs or smaller task-specific models using LoRA, QLoRA, or PEFT.
  • Professional experience integrating AI capabilities into production systems or mission applications.

 Preferred Qualifications:

  • Familiarity with agentic frameworks (LangGraph, AutoGen, CrewAI, DSPy) and multi-agent reasoning.
  • Understanding of prompt engineering, retrieval quality, and grounding methods.
  • Exposure to GPU-based or edge inference environments.
  • Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related technical field.
  • Active Secret clearance preferred; ability to obtain one is required.

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