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Intern Computer Vision Deep Learning Engineer Jobs in Missouri

Whiterabbit.ai

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... applications of computer vision Must Have Experience * Experience with deep learning and ...

Whiterabbit.ai

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... applications of computer vision Must Have Experience * Experience with deep learning and ...

Whiterabbit.ai

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... applications of computer vision Must Have Experience * Experience with deep learning and ...

Whiterabbit.ai

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... applications of computer vision Must Have Experience * Experience with deep learning and ...

Whiterabbit.ai

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... applications of computer vision Must Have Experience * Experience with deep learning and ...

Jobgether

This is an opportunity for an ML engineer who enjoys deep technical challenges, experimentation ... Accountabilities As a Machine Learning Engineer focused on Distillation, you will design, develop ...

Jobgether

$88K - $106K/yr

You will dive deep into performance optimization, from model architecture and GPU execution to ... Accountabilities As a Machine Learning Engineer specializing in inference optimization, you will ...

Jobgether

At least 5 years of professional experience developing production-grade software engineering and deep learning solutions. * Degree in Computer Science, Data Science, Machine Learning, or a related ...

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Intern Computer Vision Deep Learning Engineer information

What is the difference between Intern Computer Vision Deep Learning Engineer vs Intern Machine Learning Engineer?

AspectIntern Computer Vision Deep Learning EngineerIntern Machine Learning Engineer
Required SkillsComputer vision, deep learning, CNNs, Python, TensorFlow/PyTorchMachine learning, algorithms, Python, scikit-learn, TensorFlow/PyTorch
Work EnvironmentResearch labs, tech companies, startups focusing on image/video analysisTech companies, research labs, startups working on diverse ML applications
Industry UsagePrimarily in computer vision projects like object detection, image segmentationBroader ML projects including predictive modeling, NLP, recommendation systems

Intern Computer Vision Deep Learning Engineers focus on image and video analysis using deep learning techniques, while Intern Machine Learning Engineers work on a wider range of ML applications. Both roles require strong Python skills and familiarity with deep learning frameworks, but their project focus and industry applications differ.

What types of projects or tasks can I expect to work on as an Intern Computer Vision Deep Learning Engineer?

As an Intern Computer Vision Deep Learning Engineer, you can expect to contribute to projects involving image or video analysis, such as object detection, image classification, or facial recognition. Your daily tasks might include data preprocessing, annotating datasets, training and evaluating deep learning models, and assisting with model optimization for deployment. You’ll often work closely with senior engineers and researchers, gaining hands-on experience with real-world datasets and cutting-edge frameworks. Collaboration with cross-functional teams, such as software developers and product managers, is common to ensure your models address practical business needs.

What does an Intern Computer Vision Deep Learning Engineer do?

An Intern Computer Vision Deep Learning Engineer assists in developing and improving algorithms that enable computers to interpret and understand visual information from the world, such as images and videos. They often work on tasks like image classification, object detection, and facial recognition using deep learning frameworks like TensorFlow or PyTorch. Interns typically help with data collection, model training, evaluation, and sometimes deployment, all under the guidance of experienced team members. This role is a great opportunity to gain hands-on experience in machine learning and computer vision while contributing to real-world projects.

What are the key skills and qualifications needed to thrive as an Intern Computer Vision Deep Learning Engineer, and why are they important?

To thrive as an Intern Computer Vision Deep Learning Engineer, you need a solid understanding of machine learning fundamentals, computer vision concepts, and proficiency in programming languages like Python, often supported by coursework or personal projects. Familiarity with deep learning frameworks such as TensorFlow or PyTorch and experience with image processing libraries like OpenCV are typically expected. Strong problem-solving abilities, curiosity, and effective teamwork skills help interns excel in fast-paced research and development environments. These skills are essential for contributing to innovative projects and adapting to the rapidly evolving field of computer vision.
What are the most commonly searched types of Computer Vision Deep Learning Engineer jobs in Missouri? The most popular types of Computer Vision Deep Learning Engineer jobs in Missouri are:
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What cities in Missouri are hiring for Intern Computer Vision Deep Learning Engineer jobs? Cities in Missouri with the most Intern Computer Vision Deep Learning Engineer job openings:
Intern Computer Vision Deep Learning Engineer jobs near you
Infographic showing various Intern Computer Vision Deep Learning Engineer job openings in Missouri as of July 2026, with employment types broken down into 1% As Needed, 86% Full Time, 11% Part Time, and 2% Contract. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution.

Machine Learning Engineer with Security Clearance

SecureVision

Saint Louis, MO • On-site

Other

Re-posted 20 days ago

Job description

HOW A MACHINE LEARNING ENGINEER WILL MAKE AN IMPACT
Own your opportunity to serve as a critical component of our nation's safety and security. Make an impact by using your expertise to protect our country from threats. Job Description
Rapidly prototype containerized multimodal deep learning solutions and associated data pipelines to enable GeoAI capabilities for improving analytic workflows and addressing key intelligence questions. You will be at the cutting edge of implementing State-of-the-Art (SOTA) Computer Vision (CV) and Vision Language Models (VLM) for conducting image retrieval, segmentation tasks, AI-assisted labeling, object detection, and visual question answering using geospatial datasets such as satellite and aerial imagery, full-motion video (FMV), ground photos, and OpenStreetMap.
WHAT YOU'LL NEED TO SUCCEED:
• Education: Bachelor or Master' Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or equivalent experience in lieu of degree.
• Experience: 5+ years Technical skills:
• Demonstrated experience applying transfer learning and knowledge distillation methodologies to fine-tune pre-trained foundation and computer vision models to quickly perform segmentation and object detection tasks with limited training data using satellite imagery.
• Demonstrated professional or academic experience building secure containerized Python applications to include hardening, scanning, automating builds using CI/CD pipelines.
• Demonstrated professional or academic experience using Python to query and retrieve imagery from S3 compliant API's perform common image preprocessing such as chipping, augment, or conversion using common libraries like Boto3 and NumPy.
• Demonstrated professional or academic experience with deep learning frameworks such as PyTorch or Tensorflow to optimize convolutional neural networks (CNN) such as ResNet or U-Net for object detection or segmentation tasks using satellite imagery.
• Demonstrated professional or academic experience with version control systems such as Gitlab.
• Demonstrated experience leveraging CUDA for GPU accelerated computing. Skills and abilities desired:
• Demonstrated professional or academic experience with the HuggingFace Transformers library and hub.
• Demonstrated experience with OpenShift and container orchestration within Kubernetes using Helm, Kubectl, Kustomize, or Operators.
• Demonstrated experience with Vision Transformers (ViT) such as DINO or DeiT.
• Demonstrated academic or professional experience communicating methodological choices and model results.
• Demonstrated experience with verification and validation test benches.
• Demonstrated experience with Explainable AI (XAI) techniques.
• Demonstrated experience with Open Neural Net Exchange (ONNX).

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