
Senior Full Stack Developer for Computer Vision Models
2 days ago
As a senior member of our engineering team, you will have technical ownership of the entire platform while working with cutting-edge computer vision models at massive scale in a fast-moving, AI-first environment.
This role requires someone who can move at the speed of innovation while building systems that our users' missions depend on. If you're an AI-native engineer who thrives on technical challenges and wants to build technology that matters, we want to hear from you.
">Key Responsibilities:- Create Image Processing Pipeline: Automated systems for satellite image ingestion, preprocessing, and patch generation.
- Develop AI Model Integration Layer: Seamless integration of our object detection and classification models.
- Implement Quality Control Systems: Automated validation and human-in-the-loop review workflows.
- Design Data Management Platform: Robust database systems for storing, indexing, and retrieving intelligence data.
- Build End-User Interface: Intuitive platforms for intelligence dissemination and visualization.
- Design Scalable Infrastructure: Cloud-native architecture handling large-scale data processing.
- 5+ years of experience in software engineering with 2+ years in AI/ML system integration.
- Proven track record of leading technical teams (2-10 developers).
- Experience shipping production ML/AI systems at scale.
- Expert-level proficiency in leveraging AI coding tools (e.g., GitHub Copilot, Cursor, Claude, GPT-4).
- Demonstrated ability to use AI assistants for rapid prototyping, code generation, and debugging.
- Experience with AI-powered testing, documentation, and deployment tools.
- Track record of delivering projects 2-3x faster than traditional development approaches.
- Backend Development: Python, Node.js, or Go for high-performance systems.
- Computer Vision Integration: Experience with OpenCV, PIL, and ML model deployment (ONNX, TensorRT, TorchServe).
- Database Systems: PostgreSQL, MongoDB, or similar for geospatial and metadata storage.
- Cloud Platforms: AWS, GCP, or Azure with container orchestration (Docker, Kubernetes).
- API Development: RESTful and GraphQL APIs for system integration.
- DevOps: CI/CD pipelines, infrastructure as code, monitoring systems.
- You're obsessed with building fast and iterating quickly.
- You see AI tools as force multipliers, not just conveniences.
- You can rapidly prototype complex systems and scale them to production.
- You thrive in fast-paced, high-stakes environments.
- You understand the entire stack from data ingestion to user interfaces.
- You can architect systems that are both performant and maintainable.
- You balance speed of development with code quality and security.
- You're comfortable making technical decisions with incomplete information.
- You can effectively lead and mentor a small development team.
- You work closely with AI researchers to understand model requirements.
- You translate complex technical concepts to stakeholders.
- You're comfortable with the responsibility of mission-critical systems.
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