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Intern Computer Vision Deep Learning Engineer Jobs in Indiana

Bespoke Labs

Machine Learning Engineer

South Bend, IN · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Gary, IN · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Hammond, IN · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Fort Wayne, IN · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Evansville, IN · On-site

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

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 Indiana? The most popular types of Computer Vision Deep Learning Engineer jobs in Indiana are:
What are popular job titles related to Intern Computer Vision Deep Learning Engineer jobs in Indiana? For Intern Computer Vision Deep Learning Engineer jobs in Indiana, the most frequently searched job titles are:
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Intern Computer Vision Deep Learning Engineer jobs near you
Postdoctoral Researcher

Postdoctoral Researcher

Indiana University

Bloomington, IN • On-site

$60K/yr

Full-time

Re-posted 18 days ago

Job description

Posting Details
Position Details
Title
Postdoctoral Researcher
Appointment Status
Non-Tenure Track
Department
IU Bloomington Psychological & Brain Sciences
Location
Bloomington
Position Summary
Postdoctoral Researcher - AI-Augmented Decision Science
Indiana University Bloomington
Department of Psychological & Brain Sciences and Luddy School of Informatics, Computing, & Engineering
Position Overview
The Postdoctoral Researcher will join a new interdisciplinary project developing an AI-augmented decision science platform to understand and model high-stakes human judgments. This position will be jointly mentored by Dr. Tim Pleskac (cognitive and decision modeling) and Dr. David Crandall (computer vision and AI). The postdoc will lead the development, integration, and testing of computational models of decision making that incorporate dynamic scene features, pose tracking, and eye-tracking data collected from an immersive police shooting simulator.
The position is based at Indiana University Bloomington, with opportunities for collaboration with Michigan State University, and IU's network in cognitive modeling, AI, and human-AI decision research.
This postdoctoral appointment is full-time and on-campus.
Job Duties
80% - Research
  • Lead development of computational models of judgment and decision making, including evidence accumulation models, social drift-diffusion models, and hybrid models integrating computer-vision-derived features.
  • Build and test pipelines for pose detection, object tracking, optical-flow analysis, and gaze-scene alignment, in collaboration with computer vision researchers.
  • Analyze large multimodal datasets (simulator videos, eye-tracking videos, joint motion trajectories).
  • Lead and co-author manuscripts and conference presentations.

10% - Project Management
  • Work directly with the PIs to ensure efficient progress toward research objectives.
  • Coordinate research tasks across undergraduate RAs, graduate students, and collaborating labs.
  • Oversee data processing workflows, documentation, and reproducibility pipelines.

10% - Other Duties
  • Assist with dissemination activities, lab meetings, mentoring of junior researchers, and other project-related tasks as needed.

Required Qualifications
  • Ph.D. in Psychology, Cognitive Science, Computer Science, Data Science, Neuroscience, or a related field by the start date.
  • Demonstrated expertise in computational modeling of human behavior or computer vision / machine learning.
  • Proficiency in Python, MATLAB, or R.
  • Strong quantitative and analytic skills.

Preferred Qualifications
  • Experience with evidence-accumulation models (DDM, sequential sampling, Bayesian models).
  • Experience with computer vision tools (e.g., MediaPipe, OpenPose, homography estimation, optical flow).
  • Experience with eye-tracking data collection or analysis.
  • Familiarity with deep learning frameworks (PyTorch, TensorFlow).
  • Experience working with multimodal datasets (video, gaze, motion, behavioral responses).
  • Background or interest in decision making under uncertainty, social decision dynamics, or human-AI interaction.

Work Environment
The postdoc will be embedded in two leading research ecosystems:
The IU Behavioral Science Lab (Psychological & Brain Sciences)
A major center for judgment and decision-making research, evidence accumulation modeling, and computational cognitive science.
The Luddy School of Informatics, Computing, and Engineering
A top-tier program in computer vision, machine learning, and multimodal analytics.
The researcher will benefit from access to IU's state-of-the-art computing resources, weekly interdisciplinary meetings, and strong mentorship from both PIs.
Appointment Details
  • Anticipated Start Date: Spring or Summer 2026 (flexible)
  • Salary: $60,000 + benefits
  • Work Schedule: Full-time, on-campus
  • Supervisors: Dr. Tim Pleskac and Dr. David Crandall
  • Initial Appointment: 1 year, with expectation of renewal for a second year based on performance and funding

Application Instructions
Interested individuals should apply at https://indiana.peopleadmin.com/postings/31525.
A complete application includes:
  1. Cover letter describing research interests and fit for the position
  2. Curriculum vitae
  3. A professional writing sample (e.g., publication or dissertation chapter)
  4. Names and contact information for three references

Applications received by (1/9/2026) will receive full consideration, however the search will remain open until a suitable candidate is found.
Basic Qualifications
  • Ph.D. in Psychology, Cognitive Science, Computer Science, Data Science, Neuroscience, or a related field by the start date.
  • Demonstrated expertise in computational modeling of human behavior or computer vision / machine learning.
  • Proficiency in Python, MATLAB, or R.
  • Strong quantitative and analytic skills.

Department Contact for Questions
Dr. Tim Pleskac (tpleskac@iu.edu)
Additional Qualifications
  • Experience with evidence-accumulation models (DDM, sequential sampling, Bayesian models).
  • Experience with computer vision tools (e.g., MediaPipe, OpenPose, homography estimation, optical flow).
  • Experience with eye-tracking data collection or analysis.
  • Familiarity with deep learning frameworks (PyTorch, TensorFlow).
  • Experience working with multimodal datasets (video, gaze, motion, behavioral responses).
  • Background or interest in decision making under uncertainty, social decision dynamics, or human-AI interaction.

Salary and Rank
$60,000
Special Instructions
For Best Consideration Date
01/09/2026
Expected Start Date
03/01/2026
Posting Number
IU-101433-2025

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