We combine computer vision, edge computing, and IoT to enable autonomous checkout, real-time inventory intelligence, and frictionless store operations - bringing Amazon Golike experiences to everyday retail globally. Unlike traditional players like Zebra Technologies or Trax Retail, company built as a full-stack system across AI models, edge devices, and cloud infrastructure. We are already live across multiple locations and rapidly expanding across hospitality, gyms, and retail chains.

This is a company where :

- Engineers ship to real-world environments, not just staging

- Problems are messy, high-stakes, and deeply technical

- Ownership is absolute - you build it, you run it

- We are not optimizing for comfort.

- We are optimizing for speed, learning, and impact.

What youll do :

- Develop object detection and tracking models

- Improve accuracy vs latency trade-offs in production systems

- Optimize models for edge deployment (CPU inference, quantization)

- Solve real-world CV challenges :

1. Occlusion

2. Lighting variation

3. Dense environments

- Work closely with backend + hardware teams for deployment

Tech stack : Python, PyTorch/TensorFlow, YOLO, OpenVINO (or similar)

What were looking for :

- Strong fundamentals in computer vision and deep learning

- Ability to move from model production

- High ownership and experimentation mindset

Why this role :

- Work on real-world AI systems, not research prototypes

- Immediate feedback loop from production deployments

Compensation :

We aim to hire top-tier talent and compensate accordingly.

- Competitive salary (benchmarked against top startups)

- Meaningful ESOP ownership

- Rapid growth and learning curve

What success looks like (first 6 months) :

- You ship code/models/features to live production environments

- You take ownership of a core system or problem area

- You improve a key metric (latency, accuracy, reliability, revenue)

Hiring process :

- 2 - 3 rounds (technical + problem-solving)

- Fast turnaround (we move quickly)