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Intern Computer Vision Deep Learning Engineer Jobs in Illinois

Through custom underwater cameras, computer vision, and machine learning we are able to quantify ... Apply a combination of conventional and deep learning approaches to identify key features and ...

Staff Machine Learning Engineer - Leasing

Chicago, IL · On-site

$17.50 - $20.50/hr

... coherent technical vision that reflects real customer outcomes. * Drive the Development ... Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation ...

IL

$17.50 - $20.50/hr

... coherent technical vision that reflects real customer outcomes. * Drive the Development ... Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation ...

Lead Machine Learning Engineer

Chicago, IL

$105K - $139K/yr

You will leverage your deep understanding of modern architectures to lead the development of ... You have experience in developing a technical vision and strategy, keeping it relevant and aligned ...

Senior Data Scientist

Chicago, IL · On-site

$140K - $180K/yr

... computer vision, and other cutting-edge techniques. Key Responsibilities: * Lead advanced Data ... deep learning, and NLP. * Conduct rigorous exploratory data analysis and feature engineering to ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

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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 Illinois? The most popular types of Computer Vision Deep Learning Engineer jobs in Illinois are:
What job categories do people searching Intern Computer Vision Deep Learning Engineer jobs in Illinois look for? The top searched job categories for Intern Computer Vision Deep Learning Engineer jobs in Illinois are:
What cities in Illinois are hiring for Intern Computer Vision Deep Learning Engineer jobs? Cities in Illinois with the most Intern Computer Vision Deep Learning Engineer job openings:
Perception Engineer

Perception Engineer

Aquabyte

Mundelein, IL

$130K - $175K/yr

Full-time

Posted 28 days ago


Job description

Our mission
Aquabyte is on a mission to revolutionize the sustainability and efficiency of aquaculture. It is an audacious, and incredibly rewarding mission. By making fish farming more efficient and viable, we aim to promote healthy (for the fish and environment) production of low carbon protein and mitigate one of the biggest causes of climate change. Aquaculture is the single fastest growing food-production sector in the world, and now is the time to define how technology is used to harvest the sea and preserve it for generations to come.
 
We are a diverse, mission-driven team that is eager to work alongside kindred spirits. If this vision inspires you please get in touch.
 
Our product
We are currently focused on helping salmon farmers better understand their fish population and make environmentally sound decisions. Through custom underwater cameras, computer vision, and machine learning we are able to quantify fish weights, detect the health status, and generate optimal feeding plans in real time. Our product operates at three levels: on-site hardware for image capture, cloud pipelines for data processing, and a user-facing web application. As a result, there are hundreds of moving pieces and no shortage of fascinating challenges across all levels of the stack.
 
Above all, Aquabyte is a customer-driven company. Our product development is dictated by the needs of fish farmers and we prioritize customer delight in everything we do. We are committed to building a global, collaborative team.
 
The role
As a Perception Engineer you will help develop and deploy next-generation sensing capabilities to fish farms across the world. While our current product utilizes underwater cameras and computer vision to quantify fish health and growth, we are expanding our sensor suite to create a comprehensive understanding of the underwater environment.
Key Responsibilities
  • Signal Processing: Design and implement algorithms to process raw sensor data, correcting for environmental attenuation, noise, and physical constraints
  • Sensor Fusion & Calibration: Develop techniques to fuse multi-modal sensor streams and perform precise sensor calibration to ensure data alignment and accuracy across the hardware stack
  • 3D Scene Reconstruction: Build pipelines that generate 3D representations of the environment from complex inputs
  • Feature Detection: Apply a combination of conventional and deep learning approaches to identify key features and objects within the sensor data
  • Production Engineering: Contribute to the production codebase, ensuring algorithms are scalable, robust, and well-tested in a primarily Python-based stack
Required Qualifications
  • Educational Background: BS/MS in Robotics, Computer Science, Electrical Engineering, or a relevant technical degree
  • Experience: 3+ years of experience in perception or signal processing
  • Technical Proficiency: Strong coding ability with a mastery of Python and experience with SQL
  • Domain Expertise: Demonstrated experience with sensor fusion, state estimation, or 3D computer vision (e.g., SLAM, structure-from-motion, or point cloud processing)
  • Engineering Best Practices: Strong software engineering skills, including knowledge of testing, version control, and deployment pipelines.
Bonus Qualifications
  • Experience processing underwater acoustics or sonar data
  • Familiarity with cloud data infrastructure (e.g., Snowflake, dbt, Airflow)
  • Experience with containerization (Docker) and cloud development (AWS).
Benefits
  • Competitive salary and equity
  • Unlimited vacation policy
  • Flexible working hours + hybrid work policy
  • Medical, vision, & dental insurance
  • Retirement matching plan
  • Potential travel to Norway
  • Evolve in a fast-paced environment
  • Be able to shape a business in its early days
  • Get ideas, feedback, and suggestions from other best-in-their-field colleagues
  • Mentorship opportunities, we'll be dedicated to investing in you and supporting you as you grow
Aquabyte takes a market-based approach to compensation. The pay varies on a variety of factors including: job-related qualification, years of experience and competence level, interview performance, and work location.
At Aquabyte, we admire interesting people with a unique background. We strongly encourage you to apply even if you don’t satisfy all the requirements, and we will get back to you as soon as possible!

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.