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Machine Learning Engineer - Computer Vision

LinkedIn CaseGuard Arlington, VA
Mid-Senior level Posted March 14, 2026 Job link
Responsibilities

On the computer vision team at CaseGuard, you'll design, develop, optimize, and deploy deep learning models for tasks like object detection, tracking, video segmentation, and facial recognition, ensuring real-time performance, accuracy, and scalability. You will collect, clean, and preprocess large datasets, collaborate with software engineers, product, and cross-functional teams to integrate machine learning solutions into business processes, and deploy and monitor models in production for reliability. You’ll also stay current with advances in computer vision and AI while thoroughly documenting processes, models, and implementations for reproducibility and scalability.

Commitments

You’ll receive paid vacation and ten paid holidays per year.

Not Met Priorities
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Requirements
  • Experience in deep learning models, their training, and hyperparameter tuning using libraries such as TensorFlow, PyTorch, and Transformers or other Huggingface tools.
  • Experience with data manipulation tools such as Pandas, NumPy, and SQL.
  • Strong programming skills in Python and C++.
  • Experience in MLOps principles and model deployment and instrumentation on cloud platforms such as AWS, Azure, or Google Cloud for model deployment and knowledge with efficient serving tools such as ONNX, triton, and vllm.
  • Proficiency in working with image and video data, including preprocessing and augmentation techniques.
  • Strong understanding of machine learning algorithms, including supervised and unsupervised learning and deep learning.
  • Strong communication skills and the ability to work collaboratively in a team environment.
  • Familiarity with containerization and orchestration tools like Docker and Kubernetes.
Preferred Skills
  • Familiarity with containerization and orchestration tools like Docker and Kubernetes.
  • Experience with version control systems such as Git.
  • Understanding software engineering best practices, including code review, testing, and documentation.
  • Experience with Large Language Models (LLMs) is a great plus.
  • Experience with data annotation tools and processes.
Education
  • (Not required) – The ideal candidate will have a strong background in developing and deploying machine learning models focused on image and video processing.
  • (Not required) – Bachelor's or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.