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Intern Computer Vision Deep Learning Engineer Jobs in Illinois

Career Renew

Senior Machine Learning Engineer

Chicago, IL · Remote

$165K - $225K/yr

Design and implement novel computer vision and deep learning algorithms for virtual staining and ... Knowledge of software engineering best practices including version control (Git) and CI/CD ...

1872 Consulting

Machine Learning Engineer

Chicago, IL

Computer Vision Engineer As a Computer Vision Engineer, you will be part of our AI Team working on ... Hands-on experience applying machine learning and deep learning to vision data, preferably direct ...

Motorola

Director of Computer Vision

Tennessee, IL

Technical Vision, Engineering Leadership, and Execution: Provide executive technical leadership to ... Deep, demonstrable expertise in computer vision, machine learning algorithms, and the end-to-end ...

Motorola

Director of Computer Vision

Virginia, IL

Technical Vision, Engineering Leadership, and Execution: Provide executive technical leadership to ... Deep, demonstrable expertise in computer vision, machine learning algorithms, and the end-to-end ...

Resource Point LLC

AI/ML Engineer

Chicago, IL · On-site

Position: AI/ML Engineer Duration: 12 months Location: Chicago, IL An AI/ML Engineer designs ... Deep understanding of machine learning, deep learning, data mining, algorithms, and computer vision

GE Healthcare

Senior AI Engineer, Enterprise AI

Chicago, IL · Hybrid

$107K - $147K/yr

As the Senior AI Engineer, you will be at the forefront of developing and delivering innovative ... Computer Vision, Deep Learning, Transformers, Self-Supervised Learning, and LLM fine tuning.

NAVA Software Solutions

Sr. AI/ML Engineer

Deerfield, IL · On-site

$106K - $145K/yr

... learning, deep learning, and AI system deployment * Strong Python engineering background with ML/DL frameworks: TensorFlow, PyTorch, Keras, OpenCV * Proven experience in Computer Vision tasks ...

HERE Technologies

Sr Principal Architect

Chicago, IL · On-site

$200K - $210K/yr

Provide technical leadership across teams, mentoring architects and engineers Who are you ... Strong expertise in computer vision / deep learning (CNNs, multi-modal AI) * Strong understanding ...

IMC Inc

Principal Machine Learning Engineer

Chicago, IL

$200K - $250K/yr

Now we're expanding the team, scaling our systems, and accelerating the application of deep learning in our research and execution workflows. We're looking for a Principal Machine Learning Engineer ...

IMC

Principal Machine Learning Engineer

Chicago, IL · On-site

$200K - $250K/yr

Now we're expanding the team, scaling our systems, and accelerating the application of deep learning in our research and execution workflows. We're looking for a Principal Machine Learning Engineer ...

IMC

Principal Machine Learning Engineer

Chicago, IL

$200K - $250K/yr

Now we're expanding the team, scaling our systems, and accelerating the application of deep learning in our research and execution workflows. We're looking for a Principal Machine Learning Engineer ...

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

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 Illinois? The most popular types of Computer Vision Deep Learning Engineer jobs in Illinois are:
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Intern Computer Vision Deep Learning Engineer jobs near you

Senior Machine Learning Engineer

Career Renew

Chicago, IL • Remote

$165K - $225K/yr

Full-time

Posted 27 days ago

Job description

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus equity.
We are the leading virtual staining company revolutionizing digital pathology adoption worldwide through cutting-edge AI-powered technology. Our solutions deliver diagnostic-quality results in minutes while preserving tissue samples for comprehensive analysis.
Our breakthrough DeepStain™ and ReStain™ technologies enable unlimited virtual staining from a single tissue sample, eliminating the bottlenecks and limitations of traditional chemical staining processes. This innovation supports the critical evolution from research applications to clinical deployment, empowering laboratories to advance their digital pathology capabilities while reducing chemical waste, improving operational efficiency, and expanding diagnostic possibilities.

About the Role

We are seeking an experienced Senior ML Engineer to join our team who owns the representation-learning and generative modeling stack that powers Pictor’s virtual staining. The ideal candidate will have deep expertise in Machine Learning and building generalizable, production-ready models, and evaluations that stand up in clinical workflows.
Design and implement novel computer vision and deep learning algorithms for virtual staining and digital pathology applications
Conduct rigorous experiments to evaluate algorithm performance, validate research hypotheses, and drive iterative improvements
Develop and advance ML models leveraging Vision Transformers, Diffusion Models, GANs, and generative architectures for image-to-image translation tasks
Apply classical and learned image enhancement, denoising, and semantic segmentation techniques to histopathology imaging challenges
Explore image representation in latent space for efficient, high-fidelity virtual staining
Stay current with state-of-the-art research, identifying opportunities to apply novel techniques to PictorLabs’ product roadmap

Collaboration
Collaborate with ML Engineering and software teams to translate research prototypes into production-ready systems meeting latency and throughput requirements
Work with large-scale pathology datasets to train, validate, and fine-tune foundation models and custom architectures
Partner with software engineers, data scientists, and pathology domain experts to integrate research into production systems
Contribute to best practices for data engineering, data governance, and data quality across research and production pipelines
Leverage AI coding and ideation tools to accelerate research velocity and prototype new approaches

Required Qualifications

PhD (preferred) or Master’s degree in Computer Science, Electrical Engineering, or a related field
Deep expertise in computer vision and deep learning, with hands-on experience in one or more of: Vision Transformers, Diffusion Models, GANs, semantic segmentation, or classical image enhancement and denoising
Expert proficiency in Python and PyTorch and other scientific computing environments a plus
Strong mathematical foundation in linear algebra, probability, and optimization
Experience with large-scale model training, distributed computing, or cloud ML infrastructure (AWS, GCP, or Azure)
Knowledge of handling large scale image data, data version controls, model registry, has experience dealing with ML lifecycles
Experience with feature search, data balancing, and data curation pipelines.
Knowledge of software engineering best practices including version control (Git) and CI/CD pipelines
Excellent collaboration and communication skills, with the ability to work effectively in a fast-paced, cross-functional international startup environment
Extensive use of AI tools for coding, optimization, and ideation

Preferred Qualifications

Experience with medical imaging, digital pathology, or whole slide image (WSI) processing
Experience with LoRAs, transformer architecture and state of the art image to image translation models (Flux 2, Z-Image) and the Hugging face ecosystem
Background in generative models and fine-tuning of foundation models
Experience with GPU acceleration and optimization, including CUDA kernel engineering, TensorRT/ONNX export, and inference serving frameworks such as Triton
Experience with hosting computer vision model inference on NVIDIA DGX Spark.
Understanding of FDA regulatory requirements for AI/ML in medical devices
Experience with MLOps tools (MLflow, Kubeflow) and model versioning practices
Develop tools and frameworks to streamline ML research workflows, experimentation, and reproducibility

What We Offer

The opportunity to work on technology that directly improves patient outcomes and transforms clinical diagnostics, alongside a talented team of engineers and researchers pushing the boundaries of AI in healthcare. You will have the freedom to pursue high-impact research while seeing your work deployed at scale in real clinical environments.