
Senior AI Software Developer
1 day ago
This role involves developing a high-velocity AI platform that integrates object detection and classification models, automated systems for image ingestion and preprocessing, and quality control systems for human-in-the-loop review workflows.
The ideal candidate will have at least 5 years of experience in software engineering with a focus on AI/ML system integration, and a proven track record of leading technical teams and shipping production ML/AI systems at scale.
Key Responsibilities:- Image Processing Pipeline: Designing and implementing automated systems for satellite image ingestion, preprocessing, and patch generation.
- AI Model Integration Layer: Seamless integration of object detection and classification models to enable fast and accurate data processing.
- Quality Control Systems: Developing automated validation and human-in-the-loop review workflows to ensure data quality and integrity.
- Data Management Platform: Creating robust database systems for storing, indexing, and retrieving intelligence data.
- End-User Interface: Designing intuitive platforms for intelligence dissemination and visualization.
- Scalable Infrastructure: Building cloud-native architecture to handle large-scale data processing and ensure scalability.
- At least 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.
- 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.
A fast-paced, AI-first environment where your code will directly impact military intelligence and operations.
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