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# AI/ML Engineer I

- **Company:** GENESIS SOFTWARE INNOVATIONS, LLC
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Salary:** $120,000.0 - $150,000.0
- **Contract:** Internship / Graduate position
- **Skills:** Artificial Intelligence, Amazon Web Services, Computer Vision, Program Optimization, Nvidia CUDA, Computer Engineering, Image Analysis, Dicom, Python (Programming Language), Linux System Administration, NumPy, OpenCV, Pytorch, Deep Learning, Convolutional Neural Networks, Git, ONNX (Open Neural Network Exchange) Format, Free and Open-Source Software, Machine Learning Operations, TensorRT, Docker
- **Published:** July 8, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=9ef887d168ea6054

## About the Role

* Bachelor's in CS, Biomedical/Electrical/Computer Engineering, Applied Math, Physics, or related
 * 2+ years professional or graduate research experience in medical image analysis, computer vision, or deep learning (graduate research and internships count)
 * Proficiency in Python, PyTorch, NumPy, Git
 * Experience with at least one medical imaging library: MONAI, ITK/SimpleITK, VTK, or OpenCV
 * Familiarity with DICOM/NIfTI and 3D volumetric images (CT, MRI, X-ray)
 * Working knowledge of CNNs, U-Net, Vision Transformers, segmentation, and registration
 * Comfortable in Linux environments, * Master's in a related field
 * 3D deep learning; nnU-Net, MONAI, TorchIO, or TotalSegmentator
 * Model optimization: CUDA, TensorRT, ONNX
 * Docker and cloud (GCP/Vertex AI a plus given our current migration; AWS also relevant)
 * Reproducible ML pipelines and experiment tracking (MLflow, W&B)
 * Annotation tooling (3D Slicer, ITK-SNAP)
 * Regulated medical device development; familiarity with IEC 62304, ISO 13485, or GMLP
 * Open-source contributions or publications

## Description

You'll join our AI team to develop deep learning algorithms for image-guided interventions across the full range of radiological imaging - X-ray, CT, MRI and US. Working alongside AI scientists, software engineers, and clinicians, you'll take algorithms from research through validation and into FDA-cleared products. This is a hands-on role with broad exposure to the full ML lifecycle in a startup environment.

What You'll Do

 * Design, train, and evaluate deep learning models for segmentation, landmark detection, registration, and 3D anatomical modeling
 * Develop AI supporting image-guided interventions including surgical planning, navigation, and tumor ablation
 * Build image processing pipelines for DICOM/NIfTI volumetric data across X-ray, CT, and MRI
 * Analyze large clinical imaging datasets and improve data quality
 * Design reproducible experiments and evaluate performance with appropriate statistical methods
 * Write production-quality, well-tested code and collaborate with engineering on integration
 * Support V&V activities for regulated medical device development


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