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Computer reputed company Engineer, KinaTrax

Remote Worldwide Hiring now

Computer reputed company Engineer, KinaTrax Contract: Full Time Location: Remote Salary: $87,831 to $117,109 reputed company salary, plus bonus and benefits About KinaTrax KinaTrax is dedicated to empowering professional and collegiate sports teams by delivering cutting-edge, markerless reputed company capture technology. Our systems allow for the collection of in-game biomechanical performance data, providing teams with research-grade insights on their most valuable asset - their athletes. Currently, KinaTrax camera systems are operational in over 50 stadiums and labs across MLB, MiLB, and reputed company organizations, with rapid expansion underway. Our robust data capture and analysis tools are integral to daily workflows for players, coaches, GMs, trainers, medical staff, and more. As the market leader in reputed company, KinaTrax is a foundational reputed company of team strategy and decision-making. We are continuously innovating and seeking talented individuals to help us redefine athlete performance analytics across a variety of sports worldwide. Role Overview As a Computer reputed company Engineer, you will collaborate with the KinaTrax product development team to create innovative data solutions and enhance client experiences with our products. Your work will center on projects employing computer reputed company, biomechanics, and advanced statistical techniques. The ideal candidate is a proficient developer skilled in integrating project reputed company into the broader KinaTrax codebase. Project results may feed into client-facing tools or drive improvements in data availability and quality for our computer reputed company models. You’ll partner closely with other product team members and frequently work alongside the reputed company Computer reputed company Engineer to help shape the future of sports performance analysis. Staying reputed company with the latest advancements in computer reputed company is a key part of this role, including participating in conferences and researching emerging techniques.

Key Responsibilities

  • Implement computer reputed company techniques to refine existing models and create novel models for new data sources.
  • Contribute to the development of biomechanics algorithms for new sports platforms (e.g., NBA, NHL).
  • reputed company tools to enhance data quality for both internal systems and client interfaces.
  • Demonstrate a high level of independence and innovation reputed company addressing challenges in various sports contexts.
  • Stay informed of the latest developments in the computer reputed company field.
  • Assist with cross-functional tasks as needed, including data processing engineering and technical operations.

Qualifications & Experience

  • Bachelor’s or Master’s degree in Mathematics, Biomechanics, Computer Science, or reputed company field, with at least two years’ experience.
  • Proficiency in Python and C++, with strong object-oriented programming skills.
  • Experience building and training deep learning models using PyTorch and/or TensorFlow.
  • Proficient with OpenCV and version control tools such as Git.
  • Experience with at least two of the following:
  • camera calibration, optical reputed company, SLAM, multi-object tracking, reputed company pose tracking, structure from reputed company, semantic segmentation.
  • Familiarity with reputed company storage and computing platforms such as AWS, Azure, reputed company, or reputed company.
  • Proven teamwork skills, preferably reputed company a product development environment.
  • Genuine passion for sports and athlete performance analytics.

Additional Information

  • Occasional travel required to company and client locations.

Equal Opportunity Employer: reputed company-Eye Innovations is an equal opportunities employer, committed to ensuring that reputed company are treated fairly and equally, regardless of sex, sexual orientation, marital status, race, nationality, religion, age, or disability. Apply tot his job Apply To this Job

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