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Sports Ai Software Jobs (NOW HIRING)

AEG

Research Engineer (AI + Sports)

Pittsburgh, PA · On-site

Strong software engineering fundamentals: Python, Java, AWS, SQL, Redshift, version control ... Genuine enthusiasm for sports and AI * Genuine enthusiasm for going beyond book learning, and to ...

Dataroots BVBA

WI · On-site

The job As an AI Software Engineer at Dataroots, you play a key role in delivering end-to-end data ... Tons of team-building events and sports initiatives to stay connected and unwind. Where you'll work ...

UnternehmerTUM GmbH

$114K - $153K/yr

An atmosphere that encourages to think and experiment in new ways with software, hardware, and ... Sports membership with Wellpass to access thousands of sports facilities all over Germany (and ...

Imedica

Senior AI Engineer

Madison, WI · On-site

$120K - $158K/yr

... team sport. It's our mission to be there in the moments that matter most for our members and ... You combine strong software engineering fundamentals with hands-on experience using modern AI ...

Medica Services Company LLC

Senior AI Engineer

Madison, WI

$120K - $158K/yr

... team sport. It's our mission to be there in the moments that matter most for our members and ... You combine strong software engineering fundamentals with hands-on experience using modern AI ...

Imedica

Senior AI Engineer

Minnetonka, MN · On-site

$124K - $164K/yr

... team sport. It's our mission to be there in the moments that matter most for our members and ... You combine strong software engineering fundamentals with hands-on experience using modern AI ...

Medica

Senior AI Engineer

Minnetonka, MN · On-site

$124K - $164K/yr

... team sport. It's our mission to be there in the moments that matter most for our members and ... You combine strong software engineering fundamentals with hands-on experience using modern AI ...

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Sports Ai Software information

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$48K

$111.8K

$166K

How much do sports ai software jobs pay per year?

As of Sep 11, 2026, the average yearly pay for sports ai software in the United States is $111,845.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,000.00 and $130,000.00 per year, depending on experience, location, and employer.

What is sports AI software?

Sports AI software refers to applications that use artificial intelligence to analyze sports data, improve athlete performance, and enhance coaching decisions. These tools can process large amounts of data from games, training sessions, and biometric sensors to provide insights on player statistics, injury risks, and tactical strategies. Teams, coaches, and analysts use Sports AI software to gain a competitive edge, make informed decisions, and optimize both individual and team performance. The software is widely used across various sports, from football and basketball to tennis and athletics, and continues to evolve with advancements in AI and machine learning.

What are some common challenges faced by professionals working in sports AI software development?

Professionals in Sports AI software often encounter challenges such as managing large and complex datasets, ensuring real-time data processing for live events, and balancing accuracy with computational efficiency. Additionally, integrating AI solutions with existing sports analytics platforms and collaborating with coaches or analysts who may not have technical backgrounds can require strong communication skills. Staying updated with the latest advancements in machine learning and sports technology is also crucial for continued success in this dynamic field.

What are the key skills and qualifications needed to thrive as a sports AI software engineer, and why are they important?

To excel as a Sports AI Software Engineer, you need a strong background in computer science or a related field, proficiency in programming languages like Python or C++, and a solid understanding of machine learning algorithms. Experience with AI frameworks (such as TensorFlow or PyTorch), data analytics, and familiarity with sports data systems are typically required. Strong problem-solving, teamwork, and communication skills help you collaborate with cross-functional teams and translate complex data insights into actionable sports strategies. These abilities are vital for developing innovative AI-driven solutions that enhance performance analysis and decision-making in the sports industry.

What is the difference between Sports Ai Software vs Sports Data Analyst?

AspectSports Ai SoftwareSports Data Analyst
Required CredentialsTypically no formal degree, familiarity with AI toolsBachelor's degree in sports science, statistics, or related field
Work EnvironmentSoftware platforms, AI development environmentsOffice, sports teams, data analysis labs
Employer & Industry UsageSports tech companies, AI startups, sports analytics firmsSports teams, media outlets, analytics agencies
Common Search & ComparisonYesYes

Sports Ai Software focuses on developing and utilizing AI tools for sports analytics, often requiring technical skills in AI and software development. In contrast, Sports Data Analysts interpret data, generate reports, and provide insights using statistical tools. Both roles are integral to sports analytics but differ in technical complexity and daily tasks.

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Sports Ai Software jobs near you
Infographic showing various Sports Ai Software job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 86% Full Time, 9% Part Time, and 3% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $111,845 per year, or $53.8 per hour.

Research Engineer (AI + Sports)

Pittsburgh, PA • On-site

YinzCam Inc.
Spectator Sports • 51 - 200 employees
Learn more about YinzCam Inc.external

Full-time

Re-posted 17 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

Apply