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Remote Medical Imaging Machine Learning Jobs in Ohio

Design, develop, and implement machine learning and deep learning models * Build and optimize model ... Weekly pay with full remote flexibility * Professional growth investment, including paid ...

Design, develop, and implement machine learning and deep learning models * Build and optimize model ... Weekly pay with full remote flexibility * Professional growth investment, including paid ...

Software Engineer, Senior

Dayton, OH · On-site +1

$119K - $157K/yr

Develop and integrate machine learning workflows -- including training data preparation, model ... Background in signal processing, image processing, or remote sensing data workflows. * Experience ...

Although the position will be remote, there might be some occasional travel to ERP Suites ... Core Competencies: • Product strategy and roadmap development • AI, machine learning ...

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Showing results 41-60

Remote Medical Imaging Machine Learning information

What is a remote medical imaging machine learning specialist?

A remote medical imaging machine learning specialist is a professional who develops and applies machine learning algorithms to analyze medical images, such as X-rays, MRIs, and CT scans, from a remote location. They work with healthcare providers and researchers to improve diagnostic accuracy and streamline image analysis, often using artificial intelligence techniques. This role typically requires expertise in both medical imaging technologies and advanced machine learning, as well as the ability to collaborate virtually with multidisciplinary teams. Their work helps enable faster, more precise medical diagnoses and can contribute to advances in telemedicine.

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

To excel as a Remote Medical Imaging Machine Learning Specialist, you need a solid background in computer science, mathematics, and medical imaging, often supported by a relevant degree (such as in computer science, biomedical engineering, or a related field) and experience with machine learning frameworks. Familiarity with technical tools like Python, TensorFlow, PyTorch, and DICOM imaging systems, along with experience in medical imaging data annotation and model deployment, is typically required. Strong analytical thinking, attention to detail, and effective remote communication skills help differentiate top performers in this field. These competencies ensure the accurate development and deployment of AI models that support clinical decision-making and improve patient outcomes in healthcare environments.

How does a remote medical imaging machine learning professional typically collaborate with radiologists and other healthcare experts?

Remote Medical Imaging Machine Learning professionals work closely with radiologists, data scientists, and IT teams to develop and refine AI models for diagnostic imaging. Collaboration often occurs through virtual meetings, shared data annotation platforms, and cloud-based model deployments. Regular feedback from radiologists is essential to ensure the models provide clinically relevant and accurate outputs. This teamwork helps bridge the gap between technical development and real-world clinical needs, leading to more effective and reliable imaging solutions.
What are the most commonly searched types of Medical Imaging Machine Learning jobs in Ohio? The most popular types of Medical Imaging Machine Learning jobs in Ohio are:
What are popular job titles related to Remote Medical Imaging Machine Learning jobs in Ohio? For Remote Medical Imaging Machine Learning jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Remote Medical Imaging Machine Learning jobs in Ohio look for? The top searched job categories for Remote Medical Imaging Machine Learning jobs in Ohio are:
What cities in Ohio are hiring for Remote Medical Imaging Machine Learning jobs? Cities in Ohio with the most Remote Medical Imaging Machine Learning job openings:

AI/ML Engineer (Active TS/SCI )

Rackner

Dayton, OH • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 20 days ago


Job description

Job Title: AI/ML Engineer

Location: Dayton, OH 
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.