Computer Vision Engineer

Location: Bangalore

Experience: 3-10 years in R&D

Employment Type: Full-time or Contract

This is a research and development position requiring hands-on experience with real-world tracking projects, not theoretical knowledge alone.

About StanceBeam

Join StanceBeam, a pioneering sports technology startup revolutionising cricket through advanced computer vision and analytics. We're developing cutting-edge systems for broadcasting and Decision Review System (DRS) applications, specialising in precision ball and player tracking across cricket field distances.

This R&D-focused position offers the unique opportunity to work on real-world challenges in sports technology - from developing algorithms that track a cricket ball at 150+ km/h across 100-metre distances to creating robust player tracking systems for live broadcast and officiating.

Working directly with our CTO, you'll lead research initiatives, design innovative solutions, and implement scalable computer vision systems that are transforming how cricket is analyzed, broadcast, and officiated globally. This role is perfect for a research-minded engineer who thrives in startup environments and is passionate about pushing the boundaries of sports technology.

Role Overview

We're seeking a Computer Vision Research Engineer with proven expertise in long-distance ball and player tracking systems. This is a research-heavy role focused on developing innovative solutions for sports analytics using advanced computer vision techniques. You'll be working on challenging problems related to long-range object tracking, camera calibration for extended distances, and developing robust algorithms that work in outdoor sporting environments.

Key Responsibilities

Research & Development

• Lead R&D initiatives for long-distance ball and player tracking systems
• Research and develop novel algorithms for multi-camera tracking in outdoor sports environments
• Investigate and implement advanced camera calibration methods for long-distance applications
• Design experiments and validate tracking accuracy across different distances and conditions
• Stay current with latest research in sports computer vision and tracking technologies
• Publish research findings and contribute to technical documentation

Algorithm Development

• Develop and enhance stereo vision algorithms specifically for ball tracking at distances up to 100+ metres
• Implement robust player tracking algorithms that work across cricket field dimensions
• Optimise tracking performance under varying lighting and weather conditions
• Create calibration pipelines for multi-camera setups with long baseline configurations
• Develop real-time processing capabilities for live match scenarios

System Integration & Testing

• Collaborate with hardware team on camera placement and setup optimization
• Integrate tracking algorithms with existing sports analytics pipeline
• Conduct extensive field testing and validation of tracking systems
• Work with product team to define technical requirements and specifications

Essential Requirements

R&D Experience

• Minimum 3 years of R&D experience in computer vision, preferably in sports technology
• Proven track record of working on real-world ball tracking and/or player tracking projects
• Hands-on experience with long-distance object tracking (50+ metres)
• Published research or demonstrable projects in sports computer vision (portfolio required)

Technical Expertise

• Deep expertise in camera calibration methods for long-distance applications:
• Multi-camera calibration with large baselines
• Intrinsic and extrinsic parameter estimation
• Lens distortion correction for telephoto setups
• Camera network calibration and synchronisation
• Proven experience in tracking systems:
• Ball tracking in outdoor environments
• Multi-object player tracking
• Trajectory prediction and analysis
• Occlusion handling in crowded scenes

Technical Skills

• Advanced Python programming with computer vision libraries (OpenCV, scikit-image)
• Strong mathematics background: Linear algebra, projective geometry, optimization
• Machine learning expertise: Deep learning for object detection and tracking
• Experience with tracking frameworks: SORT, DeepSORT, or custom tracking solutions
• Camera hardware knowledge: Understanding of lens systems, sensor characteristics
• Real-time processing: Experience with performance optimization and GPU programming

Preferred Qualifications

• PhD/Master's/b.Tech in Computer Vision, Robotics, CSE or related field with focus on tracking systems
• Sports technology experience: Cricket, football, or similar field sports
• Experience with specialized cameras: High-speed cameras, telephoto lens systems
• Experience with 3D reconstruction and depth estimation from stereo systems

Specific Project Experience Required

Candidates must demonstrate experience in at least 2 of the following:

1. Ball tracking projects with tracking distances exceeding 50 metres
2. Multi-camera calibration for outdoor sports venues
3. Player tracking systems in field sports (cricket, football, etc.)
4. Long-distance stereo vision applications
5. Real-time tracking systems for live sports broadcasting

Technical Challenges You'll Solve

• Accurate ball detection and tracking across 100+ metre cricket pitches
• Robust player identification and tracking with jersey number recognition
• Camera calibration for telephoto lens setups with minimal overlap
• Handling atmospheric distortions in long-distance imaging
• Real-time processing of 4K+ video streams from multiple cameras
• Trajectory analysis and predictive modelling for ball physics

What We Offer

• Research-focused environment with access to latest technology and resources
• Direct collaboration with sports federations, leagues, and cricket boards
• Cutting-edge hardware access including high-end cameras and computing resources
• Competitive salary and equity package commensurate with R&D experience