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Full Time Computer Vision Intern Jobs (NOW HIRING)

Woodhaven Furniture

CAD Technician

Coolidge, GA · On-site

Join Woodhaven Furniture as a Full Time CAD Technician and immerse yourself in an exciting, hands ... You will have benefits such as Medical, Dental, Vision, 401(k), Life Insurance, Competitive Salary ...

Woodhaven Furniture

CAD Technician

Coolidge, GA · On-site

Join Woodhaven Furniture as a Full Time CAD Technician and immerse yourself in an exciting, hands ... You will have benefits such as Medical, Dental, Vision, 401(k), Life Insurance, Competitive Salary ...

Woodhaven Furniture

CAD Technician

Coolidge, GA · On-site

Join Woodhaven Furniture as a Full Time CAD Technician and immerse yourself in an exciting, hands ... You will have benefits such as Medical, Dental, Vision, 401(k), Life Insurance, Competitive Salary ...

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Full Time Computer Vision Intern information

What is the difference between Full Time Computer Vision Intern vs Full Time Machine Learning Intern?

AspectFull Time Computer Vision InternFull Time Machine Learning Intern
Required CredentialsCurrently pursuing or recently completed a degree in Computer Science, Electrical Engineering, or related fields; knowledge of computer vision librariesSimilar educational background; familiarity with machine learning frameworks like TensorFlow or PyTorch
Work EnvironmentResearch labs, tech companies, or startups focusing on image/video analysisTech companies, research institutions working on predictive models and data analysis
Employer & Industry UsageCommon in AI, robotics, autonomous vehicles, and multimedia industriesUsed across AI, data science, and software development sectors

Both roles involve internships in AI-related fields with overlapping skills, but Computer Vision Interns focus on image and video processing, while Machine Learning Interns work on broader predictive models. The choice depends on your specific interest in visual data versus general algorithms.

What types of projects and technologies do Full Time Computer Vision Interns typically work on, and how do they collaborate with other team members?

As a Full Time Computer Vision Intern, you can expect to work on projects involving tasks like image classification, object detection, or video analysis, often using frameworks such as TensorFlow or PyTorch. Interns commonly assist in dataset preparation, model training, and performance evaluation. Collaboration is key—you'll work closely with data scientists, software engineers, and sometimes product managers to integrate computer vision solutions into real-world applications. Regular team meetings, code reviews, and brainstorming sessions help interns learn best practices and contribute effectively while building valuable professional relationships.

What does a Full Time Computer Vision Intern do?

A Full Time Computer Vision Intern assists in developing algorithms and models that allow computers to interpret and process visual information from the world, such as images and videos. Their responsibilities often include data preprocessing, contributing to machine learning model training, and evaluating the performance of computer vision systems. They may also collaborate with other engineers and scientists to research and implement new techniques in areas like object detection, image classification, or image segmentation. This role provides hands-on experience with popular tools, frameworks, and real-world datasets, preparing interns for advanced roles in artificial intelligence and computer vision.

What are the key skills and qualifications needed to thrive as a Full Time Computer Vision Intern, and why are they important?

To thrive as a Full Time Computer Vision Intern, you need a solid grounding in computer science fundamentals, linear algebra, and experience with machine learning and image processing algorithms, typically supported by coursework or a degree in a related field. Familiarity with programming languages like Python or C++, deep learning frameworks such as TensorFlow or PyTorch, and version control systems like Git is highly valued. Strong analytical thinking, problem-solving abilities, and effective communication skills help interns collaborate with teams and convey technical concepts clearly. These skills and qualities are essential for developing innovative solutions, contributing to research, and adapting quickly in a fast-evolving field.
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What are the most commonly searched types of Computer Vision Intern jobs? The most popular types of Computer Vision Intern jobs are:
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Full Time Computer Vision Intern jobs near you
Infographic showing various Full Time Computer Vision Intern job openings in the United States as of June 2026, with employment types broken down into 95% Part Time, and 5% Contract. Highlights an 95% Physical, 2% Hybrid, and 3% Remote job distribution.
Senior Software Engineer, Computer Vision

Senior Software Engineer, Computer Vision

Knightscope

Sunnyvale, CA

$175K - $210K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 14 days ago

Job description

About Knightscope

Knightscope is a security technology company building the Nation's First Autonomous Security Force. The Company combines autonomous machines, advanced software, and human expertise to help protect people, property, and critical infrastructure. Knightscope's long-term mission is to make the United States of America the safest country in the world.


About the Role

We are looking for a Senior Software Engineer to design, develop, and deploy computer vision systems that turn continuous video, audio, and sensor streams into reliable security intelligence. Your work will directly impact the safety and operational effectiveness of deployed security platforms across hundreds of real-world sites. You will collaborate with embedded, cloud, and product teams to deliver perception capabilities that power real-time threat detection and response.


Location Requirement: Full-time, on-site at Sunnyvale HQ (no relocation provided)


Key Responsibilities

  • Design and own the end-to-end ML pipeline for security perception: data ingestion, annotation, model training, evaluation, and deployment across edge and cloud targets.
  • Develop and deploy computer vision models for real-time security intelligence, spanning detection, tracking, recognition, and classification, on embedded GPU hardware.
  • Build and maintain data flywheel and active learning pipelines that leverage fleet-scale production data to drive continuous model improvement.
  • Optimize and deploy models to edge hardware using TensorRT, INT8/FP16 quantization, and hardware-aware model design for NVIDIA Jetson platforms.
  • Define evaluation frameworks and metrics to measure model performance in production, identify failure modes, and drive reliability improvements.
  • Collaborate with embedded, cloud, and product teams to integrate perception outputs into the security incident pipeline.
  • Support on-robot integration, debugging, and validation in real-world environments


Required Qualifications

  • 5+ years shipping computer vision or ML systems to production in physical security, video analytics, surveillance, automotive, or robotics domains.
  • Deep expertise in one or more areas: object detection, video analytics, multi-camera tracking, audio classification, or edge AI inference.
  • Strong ML engineering in Python and C++ with hands-on experience in PyTorch or TensorFlow, model optimization, and production deployment.
  • Understanding of camera systems, image processing, ISP pipelines, and sensor characteristics as they affect model design and performance.
  • Experience deploying ML models on embedded GPU platforms such as NVIDIA Jetson or equivalent under real-world latency and power constraints.

Preferred Qualifications

  • Experience with GPU-accelerated video analytics frameworks such as NVIDIA DeepStream or equivalent.
  • Familiarity with camera SoC hardware, ISP pipelines, and system-level trade-offs for edge AI.
  • Background in active learning, data flywheel design, or large-scale dataset curation for production CV systems.
  • Familiarity with VLM or multimodal AI approaches for scene understanding and anomaly detection in security contexts.
  • Familiarity with cloud ML infrastructure: training orchestration, model registries, and OTA model deployment for fleet systems.
  • MS or PhD in Computer Science, Electrical Engineering, Machine Learning, or related field.

Compensation & Benefits

  • Base Salary:$175,000 to $210,000 base (DOE)
  • Equity:Stock options
  • Benefits:Medical, dental, vision, 401(k), paid time off
  • Location Requirement:Full-time, on-site at Sunnyvale HQ

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