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Remote Machine Learning Compiler Engineer Jobs in Ohio

... and Remote Employment Type: Full-Time Clearance requirements: TS/SCI About the Role Rackner is seeking a highly skilled AI/ML Engineer to design, develop, and deploy advanced machine learning ...

AI ML Engineer Location: Mason, OH (Remote) Job Type: Fulltime Must Have Technical/Functional ... Machine Learning & Model Training * Training, evaluation, fine tuning * Tagging and labeling ...

Digital - Principal SRE (AI Engineer)

Columbus, OH ยท On-site +1

$55 - $73.25/hr

Collaborate with cross-functional teams to integrate machine learning models into production ... Remote roles will also have the opportunity to come together in our offices for moments that matter.

Digital - Principal SRE (AI Engineer)

Columbus, OH ยท On-site +1

$53.50 - $71.25/hr

Collaborate with cross-functional teams to integrate machine learning models into production ... Remote roles will also have the opportunity to come together in our offices for moments that matter.

Digital - Principal SRE (AI Engineer)

Columbus, OH ยท On-site +1

$53.50 - $71.25/hr

Collaborate with cross-functional teams to integrate machine learning models into production ... Remote roles will also have the opportunity to come together in our offices for moments that matter.

Digital - Principal SRE

Columbus, OH ยท On-site +1

$53.50 - $71.25/hr

Collaborate with cross-functional teams to integrate machine learning models into production ... Remote roles will also have the opportunity to come together in our offices for moments that matter.

Digital - Principal SRE

Columbus, OH ยท On-site +1

$55 - $73.25/hr

Collaborate with cross-functional teams to integrate machine learning models into production ... Remote roles will also have the opportunity to come together in our offices for moments that matter.

Digital - Principal SRE

Columbus, OH ยท On-site +1

$53.50 - $71.25/hr

Collaborate with cross-functional teams to integrate machine learning models into production ... Remote roles will also have the opportunity to come together in our offices for moments that matter.

AI and Data Science Engineer III

Cincinnati, OH ยท On-site +1

$109K - $131K/yr

Deliver governed datasets and feature engineering and serving patterns for machine learning training and real-time inference, including online and offline consistency, caching, latency targets, and ...

AI and Data Science Engineer III

Cleveland, OH ยท On-site +1

$111K - $133K/yr

Deliver governed datasets and feature engineering and serving patterns for machine learning training and real-time inference, including online and offline consistency, caching, latency targets, and ...

$93K - $128K/yr

Sr. RAN Engineer- Remote, Canada The Select Group is seeking an experienced RAN Engineer to join a ... Familiarity with data science and machine learning techniques - especially anomaly detection and ...

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Showing results 1-20

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:
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:
AI/ML Engineer (Active TS/SCI )

AI/ML Engineer (Active TS/SCI )

Rackner

Dayton, OH โ€ข On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 2 days ago


Job description

Job Title: AI/ML Engineer

Location: Dayton, OH and Remote
Employment Type: Full-Time

Clearance requirements: TS/SCI

About the Role

Rackner is seeking a highly skilled AI/ML Engineer to design, develop, and deploy advanced machine learning solutions that support mission-critical systems. This role will focus on building scalable models, developing training pipelines, and collaborating with cross-functional teams to deliver impactful AI-driven solutions.

Key Responsibilities

  • Design, develop, and implement machine learning and deep learning models
  • Build and optimize model architectures including CNNs, RNNs, and transformer-based models
  • Develop and deploy Large Language Models (LLMs) and object detection systems (e.g., YOLO, Faster R-CNN)
  • Perform feature engineering and prepare high-quality datasets for training and evaluation
  • Create and maintain AI/ML training runbooks and documentation
  • Collaborate with data engineers and software teams to integrate models into production systems
  • Ensure reproducibility through data versioning and metadata standards
  • Continuously evaluate and improve model performance and scalability

Required Qualifications

  • Strong proficiency in designing and implementing model architectures, including:
    • Convolutional Neural Networks (CNNs)
    • Recurrent Neural Networks (RNNs)
    • Transformer-based architectures
    • Large Language Models (LLMs)
    • Object Detection models (e.g., YOLO, Faster R-CNN)
  • Hands-on experience with:
    • PyTorch and/or TensorFlow
    • Hugging Face, Ollama, or similar frameworks
  • Experience with data engineering concepts, including:
    • Feature engineering and dataset preparation
    • Data versioning tools (e.g., lakeFS)
    • Metadata standards such as STAC
  • Ability to create clear and effective AI/ML training runbooks
  • Strong problem-solving skills and ability to work in a collaborative environment

Preferred Qualifications

  • Experience deploying models in cloud-native environments
  • Familiarity with DevSecOps practices
  • Experience working with large-scale or federal datasets
  • Understanding of MLOps principles and pipelines

Benefits & Perks

  • Weekly pay with full remote flexibility
  • Professional growth investment, including paid certifications and training
  • Comprehensive benefits package, including:
    • Medical, dental, and vision coverage
    • 401(k) with 100% company match up to 6%
    • Paid time off (PTO)
    • Life and disability insurance
    • Home office equipment plan
  • A supportive, inclusive team culture focused on collaboration, trust, and mission impact

About Rackner

Rackner is a cloud-native software consultancy delivering solutions for startups, enterprises, and the public sector.

We enable digital transformation through DevSecOps, AI/ML, and cloud-first innovation.

Our teams solve high-impact problems that advance federal missions and strengthen national readiness.

Join us to help shape the future of secure, scalable data systems supporting mission success.