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Entry Level Computer Vision Engineer Jobs in Pittsburgh, PA

Research Engineer

Pittsburgh, PA ยท On-site +1

$122K - $215K/yr

You will work closely with our team of world-renowned scientists and engineers specializing in deep learning, computer vision, and self-driving technologies to develop cutting-edge solutions that ...

Research Engineer

Pittsburgh, PA ยท On-site +1

$122K - $215K/yr

You will work closely with our team of world-renowned scientists and engineers specializing in deep learning, computer vision, and self-driving technologies to develop cutting-edge solutions that ...

Engineer

Pittsburgh, PA ยท On-site

$100K - $120K/yr

Skill: AI Engineer Must Have Technical/Functional Skills: * Programming Languages: Strong ... Integrate pre-trained AI models, LLMs, and computer vision tools into existing company software and ...

Research Engineer

Pittsburgh, PA ยท On-site

$100K - $300K/yr

Position Overview We are hiring Research Engineers to develop scalable robotic systems aimed at ... computer vision. * Experience working with robot systems and large-scale model training. Base ...

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Entry Level Computer Vision Engineer information

See Pittsburgh, PA salary details

$45.3K

$113.5K

$128.5K

How much do entry level computer vision engineer jobs pay per year?

As of Aug 5, 2026, the average yearly pay for entry level computer vision engineer in Pittsburgh, PA is $113,547.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,200.00 and $122,900.00 per year, depending on experience, location, and employer.

What does an entry level computer vision engineer do?

An Entry Level Computer Vision Engineer assists in developing computer systems that can interpret and process visual information from the world, such as images and videos. They typically work with machine learning algorithms, neural networks, and image processing techniques to solve problems like object detection, facial recognition, and image classification. Their work often involves data annotation, model training, testing, and optimizing algorithms under the guidance of senior engineers. Entry level engineers usually have a background in computer science or related fields and are familiar with programming languages such as Python and libraries like OpenCV and TensorFlow.

What is the difference between Entry Level Computer Vision Engineer vs Computer Vision Analyst?

AspectEntry Level Computer Vision EngineerComputer Vision Analyst
Required CredentialsBachelor's in CS, Electrical Engineering, or related; knowledge of ML and CV frameworksBachelor's in CS, Data Science, or related; strong analytical skills
Work EnvironmentTech companies, R&D labs, startups; focus on developing algorithms and modelsData analysis teams, research firms; focus on interpreting CV data and insights
Employer & Industry UsageTech, automotive, robotics, healthcareMarket research, consulting, security, and surveillance

Entry Level Computer Vision Engineers focus on developing and implementing computer vision algorithms, often working in R&D or product teams. In contrast, Computer Vision Analysts primarily interpret and analyze CV data to generate insights. Both roles require a strong technical background, but their daily tasks and industry applications differ.

What types of projects do entry level computer vision engineers typically work on, and how much collaboration is involved?

Entry level computer vision engineers often work on tasks like annotating datasets, developing and testing algorithms for image or video analysis, and supporting the integration of computer vision models into existing applications. These projects usually require close collaboration with data scientists, senior engineers, and sometimes product managers to ensure models meet performance requirements. It's common to participate in code reviews and team meetings, fostering a supportive learning environment. As you gain experience, you'll likely take on more complex responsibilities and contribute to larger project components.

What are the key skills and qualifications needed to thrive as an entry level computer vision engineer, and why are they important?

To thrive as an Entry Level Computer Vision Engineer, you need a solid background in computer science, mathematics, and image processing, often supported by a relevant degree. Familiarity with programming languages like Python or C++, experience with deep learning frameworks (such as TensorFlow or PyTorch), and knowledge of OpenCV are typically required. Strong problem-solving abilities, attention to detail, and effective teamwork set top candidates apart. These skills and tools are essential for developing, optimizing, and implementing computer vision solutions in real-world applications.
What are the most commonly searched types of Computer Vision Engineer jobs in Pittsburgh, PA? The most popular types of Computer Vision Engineer jobs in Pittsburgh, PA are:
What are popular job titles related to Entry Level Computer Vision Engineer jobs in Pittsburgh, PA? For Entry Level Computer Vision Engineer jobs in Pittsburgh, PA, the most frequently searched job titles are:
What job categories do people searching Entry Level Computer Vision Engineer jobs in Pittsburgh, PA look for? The top searched job categories for Entry Level Computer Vision Engineer jobs in Pittsburgh, PA are:
What cities near Pittsburgh, PA are hiring for Entry Level Computer Vision Engineer jobs? Cities near Pittsburgh, PA with the most Entry Level Computer Vision Engineer job openings:
Infographic showing various Entry Level Computer Vision Engineer job openings in Pittsburgh, PA as of July 2026, with employment types broken down into 86% Full Time, and 14% Temporary. Highlights an 86% In-person, and 14% Remote job distribution, with an average salary of $113,547 per year, or $54.6 per hour.

Research Engineer (AI + Sports)

YinzCam Inc.

Pittsburgh, PA โ€ข On-site

Full-time

Posted 9 days ago


Job description

Description
YinzCam is seeking exceptional Research Engineers to lead the development of AI-driven video analysis and game analytics systems that power next-generation fan experiences in professional sports. This is a rare opportunity to conduct publishable research while building products that reach millions of fans in real time.
You'll work at the cutting edge of computer vision and machine learning applied to sports, collaborating with leading academic researchers at Carnegie Mellon University while taking your innovations from prototype to production. This role demands both research rigor and product sensibility. We value publication records and engineering excellence equally. This is a full-time, onsite position based in Pittsburgh, PA.
You will be at the forefront of establishing a new, in-house AI Research Lab within YinzCam, and working with multiple sports teams, leagues, and venues to apply AI to the fan experience and to business operations.
CORE RESPONSIBILITIES.
Video Analysis & Computer Vision
  • Design and develop AI systems for real-time video understanding of live sporting events (player detection, action recognition, spatial analysis, etc.)
  • Build robust computer vision pipelines that handle challenging real-world footage (lighting, occlusion, multiple camera angles)
  • Explore novel architectures and techniques in modern CV to solve sports-specific problems

Large-Scale Game Analytics
  • Develop AI systems to extract, aggregate, and interpret game data at scale across multiple sports, teams, and seasons
  • Create spatial and temporal analytics frameworks that surface actionable insights from video and sensor data
  • Build analytics platforms that scale from single games to league-wide deployments

AI-Powered Fan Experiences
  • Translate video understanding and analytics into engaging, intuitive experiences for millions of fans
  • Collaborate on product features that leverage AI (real-time highlights, personalized stats, interactive visualizations, etc.)
  • Ensure research outputs move through the full product development lifecycle

CORE GOALS.
  1. Publish Your Work: We intend to publish the work coming out of these research projects. Papers will be published in top-tier CV/ML venues and presented at conferences.
  2. Bridge Academia & Industry: Work directly with Prof. Priya Narasimhan (Carnegie Mellon University) and her research team to translate academic innovations into applied systems. Mentor CMU students, collaborate on research projects, and shape the next generation of sports AI researchers.
  3. From Research to Product: Own the path from prototype to production. You'll participate in design reviews, handle real-world deployment challenges, and see your ideas impact actual fan experiences at scale.

CORE REQUIREMENTS.
  • PhD in Computer Vision, Machine Learning, Computer Science, or a closely related field
  • Strong publication track record in top-tier venues (CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, etc.)
  • Deep expertise in modern computer vision techniques: neural networks, object detection, semantic/instance segmentation, action recognition, optical flow, pose estimation, or related areas
  • Proficiency in ML frameworks (PyTorch, TensorFlow) and modern deep learning practices
  • Strong software engineering fundamentals: Python, Java, AWS, SQL, Redshift, version control, testing, CI/CD
  • Demonstrated ability to implement complex systems end-to-end
  • Background in sports analytics, sports tech, or applied computer vision (industry, research, or both)
  • Genuine enthusiasm for sports and AI
  • Genuine enthusiasm for going beyond book learning, and to have ideas go into large-scale production

HOW TO APPLY
Please submit:
  1. Your CV (with publication list) and research statement.
  2. A cover letter describing your research interests and why you're excited about this opportunity
  3. Links to your top 2-3 publications hat best represent your work