iOS Computer Vision Engineer (Sports Video Analysis)

iOS Computer Vision Engineer – Sports Video Analysis

Position Responsibilities & Expected Results

We are looking for an experienced iOS Engineer specializing in Computer Vision and Video Analysis to develop a general-purpose sports movement analysis engine for our existing native iOS application.

Key responsibilities:

• Integrate Apple's Vision framework and Google MediaPipe for human pose estimation, body tracking, and keypoint detection.
• Design reusable video analysis components supporting different sports, exercises, and movement patterns.
• Develop algorithms to calculate biomechanical metrics, including joint angles, range of motion, movement velocity, and distances.
• Implement exercise recognition, repetition counting, movement classification, and technique evaluation.
• Develop algorithms to identify movement patterns, detect incorrect techniques, and assess movement quality.
• Support real-time video analysis and post-recording video processing.
• Optimize video processing for accuracy, speed, and resource efficiency on iOS devices.
• Evaluate and improve analysis reliability under different camera angles, lighting conditions, and recording environments.
• Build modular, scalable, and maintainable architectures and ensure proper testing and documentation.

Expected results:

• A reliable, extensible video analysis engine integrated into the existing iOS application.
• Accurate human movement tracking and biomechanical measurements.
• Reusable algorithms for analyzing different sports and exercises.
• Efficient video processing and continuously improving analysis accuracy.

Team & Reporting Structure

The candidate will join the iOS development team and report directly to the Engineering Manager.

They will collaborate with existing iOS developers, providing technical guidance and establishing best practices for computer vision implementation.

The role also involves working with sports scientists, coaches, and performance analysts to translate sports science requirements into practical algorithms and validate analytical results.

Challenges & Growth Opportunities

This role offers the opportunity to build a sophisticated sports video analysis system and solve real-world computer vision and movement analysis challenges.

Key opportunities include:

• Developing a general-purpose engine for diverse sports and movement patterns.
• Transforming raw computer vision outputs into meaningful biomechanical insights.
• Improving tracking accuracy under challenging recording conditions.
• Balancing analytical accuracy with mobile processing performance.
• Exploring emerging computer vision technologies and techniques.
• Collaborating with sports science professionals to validate analysis results.
• Taking technical ownership and influencing the architecture and future direction of the platform.
• The position offers opportunities to grow expertise in computer vision, biomechanics, mobile AI, and sports technology.

Essential Knowledge & Additional Skills

Required qualifications:

• Strong experience in native iOS development using Swift.
• Knowledge of iOS architecture, video processing, camera APIs, and multimedia frameworks.
• Practical experience with Apple's Vision framework and/or Google MediaPipe.
• Understanding of computer vision, human pose estimation, object tracking, and keypoint detection.
• Experience working with video frames, coordinate systems, skeletal representations, and spatial data.
• Strong algorithm development skills, including geometry, trigonometry, and motion analysis.
• Understanding of biomechanics, joint angles, range of motion, and movement trajectories.
• Experience with mobile performance optimization, asynchronous processing, and multithreading.
• Ability to write clean, modular, testable, and maintainable code.

Additional advantages:

• Experience in sports technology, fitness applications, or biomechanics.
• Familiarity with Core ML and on-device AI inference.
• Experience with real-time video processing and OpenCV.
• Experience developing movement recognition, classification, and repetition-counting algorithms.
• Familiarity with Python and data analysis for algorithm prototyping and validation.
• Experience evaluating computer vision accuracy using annotated datasets.
• Experience working with pre-trained models and adapting their outputs to specific sports and movement requirements is particularly valuable. Training custom ML models is not a primary requirement.