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Intern Computer Vision Deep Learning Engineer Jobs in Kentucky

Jobzhr

$180 - $280/hr

We're hiring our Founding Machine Learning Engineer (MLE) with expertise in Agent Development and ... Deep understanding of agent evaluation techniques (reliability, safety, success metrics) * Up-to ...

New

NVIDIA Corporation

$124 - $242/hr

Master's or PhD in Computer Science, Electrical Engineering or related field - or equivalent ... Deep Learning, Artificial Intelligence, and Large Language Models. If you're a creative engineer ...

New

S27a

$140 - $210/hr

Develop, test, and modify computer programs to apply machine learning models to real-world ... Experience with modern deep learning models, particularly large language models (LLMs) and ...

New

Nerdleveltech

$230 - $322/hr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... on a long-term vision for Shopping Ads delivery. Preferred qualifications * Experience with ... Experience with deep learning architectures such as multi-task models, sequence models ...

Toyota

Physical AI Senior Engineer

Georgetown, KY

$94K - $129K/yr

  • Medical

  • Retirement

  • PTO

Computer vision (e.g., detection, segmentation, 3D perception) * Machine learning / deep learning * Robotics * Proficiency in Python, C++, ROS-based systems; strong software engineering fundamentals.

Toyota Motor Sales

Physical AI Senior Engineer

Georgetown, KY · On-site

$94K - $129K/yr

  • Medical

  • Retirement

  • PTO

Computer vision (e.g., detection, segmentation, 3D perception) * Machine learning / deep learning * Robotics * Proficiency in Python, C++, ROS-based systems; strong software engineering fundamentals.

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All JobsIntern Computer Vision Deep Learning Engineer JobsIntern Computer Vision Deep Learning Engineer Jobs in Kentucky

Intern Computer Vision Deep Learning Engineer information

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?

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 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 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 are popular job titles related to Intern Computer Vision Deep Learning Engineer jobs in Kentucky?

For Intern Computer Vision Deep Learning Engineer jobs in Kentucky, the most frequently searched job titles are:

What job categories do people searching Intern Computer Vision Deep Learning Engineer jobs in Kentucky look for?

The top searched job categories for Intern Computer Vision Deep Learning Engineer jobs in Kentucky are:

Intern Computer Vision Deep Learning Engineer jobs near you

Founding Machine Learning Engineer [32934]

Jobzhr

On-site

$180 - $280/hr

Other

This job post has expired today. Applications are no longer accepted.

Job description

We're hiring our Founding Machine Learning Engineer (MLE) with expertise in Agent Development and Time-Series Modeling. You'll play a foundational role in building production-grade systems that combine the power of LLM-powered agents with time-series foundation models.

The Role

This is not a narrow research role - you'll design, train, deploy, and monitor ML systems end-to-end, moving from prototype to production with speed and autonomy. You'll also be a core contributor to defining how agents interact with multimodal numerical data, a problem space where the playbook does not yet exist.

Job Description:
  • Design, train, and deploy production ML systems (LLM-powered agents + time-series models)
  • Build and scale LLM-powered agents with advanced capabilities: multi-step reasoning, tool integration, autonomous workflows, memory/context management, and adaptive strategies
  • Develop and refine evaluation frameworks for agents, ensuring reliability, safety, and measurable performance
  • Apply and extend time-series modeling techniques (forecasting, anomaly detection, multimodal fusion) in real-world customer scenarios
  • Operate end-to-end: from data ingestion and preprocessing to deployment, monitoring, and continuous improvement
  • Stay ahead of the curve on the latest innovations in AI agents, orchestration frameworks, and infrastructure (MCP, A2A, etc.)
  • Partner directly with researchers, engineers, and lighthouse customers to validate solutions and drive rapid iteration
What we're looking for:
  • Proven industry experience (4-10 years) as an ML Engineer, Research Engineer, or Applied Scientist, with a track record of shipping production ML systems
  • Hands-on expertise in LLM-powered agents: multi-step reasoning, tool use, context windows, autonomous workflows, agent memory
  • Deep understanding of agent evaluation techniques (reliability, safety, success metrics)
  • Up-to-date with modern agent infrastructure and frameworks (MCP, A2A, etc.)
  • Fluency with ML engineering best practices: reproducibility, monitoring, scaling, CI/CD, observability
  • Comfort operating in a fast-paced startup: shipping quickly, making tradeoffs, and thriving in ambiguity
Nice to have:
  • Experience training custom neural networks beyond pre-trained LLMs (e.g., transformers for time-series or multimodal data)
  • A background in time-series modeling (forecasting, anomaly detection, classical + deep learning approaches)
  • Published research or open-source contributions in ML/AI
Location & Sponsorship
  • Location: San Francisco Bay Area, CA (in-person)
  • Visa Sponsorship: H1-B, O1
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