About the Role - COMPUTER VISION ENGINEER
We are looking for a skilled and passionate Computer Vision Engineer to join our growing engineering team. You will be responsible for building, optimizing, and deploying production-grade computer vision systems on edge and cloud infrastructure. You will work across the full stack — from model inference pipelines to system-level deployment — ensuring our vision platform is fast, secure, and reliable at scale.
Key Responsibilities
- Design and deploy end-to-end computer vision pipelines optimized for real-time inference on GPU-accelerated hardware.
- Own system packaging, installation, and fleet rollout processes, including dependency management, service configuration, and upgrade strategies.
- Implement and maintain security hardening practices across deployed systems, including encryption key management, file permission audits, and hardware security integrations.
- Optimize model inference performance through hardware-accelerated encoding/decoding pipelines, model compilation tooling, and efficient similarity search indexing.
- Build and maintain operational observability across the vision platform, including structured logging, health checks, metrics collection, and alerting.
- Collaborate with cross-functional teams to define deployment standards and conduct system retrospectives to continuously improve reliability.
Requirements
- 1+ years of experience in computer vision engineering or a related field.
- Proficiency in Python and working knowledge of C++.
- Exposure to GPU-accelerated inference and hardware video pipelines.
- Basic familiarity with Linux system administration, service management, and package deployment workflows.
- Awareness of security best practices in embedded or edge computing environments.
- Eagerness to learn vector search, large-scale similarity search, and model optimization techniques.
- Strong problem-solving mindset with attention to logging and system observability.
Work Location: In person
