Job Summary:
Oslitandi Tech LLC is focused on unifying sustainable technology solutions for clients. They are seeking a Lead AI Engineer to create core AI capabilities, architect deep learning models, and develop advanced sensor fusion algorithms for critical operations.
Responsibilities:
• Architect, design, and train advanced deep neural networks (e.g., CNNs, Transformers, R-CNN variants) specifically optimized for object detection, classification, and tracking across multi-modal sensor inputs (e.g., High-resolution Optical, SAR, Radar).
• Lead the development and implementation of advanced sensor fusion algorithms, including extended and unscented Kalman Filtering and particle filters, to reliably correlate and maintain track continuity from disparate, asynchronous data sources (e.g., Radar + Electro-Optical/IR + ADS-B).
• Conduct model optimization, pruning, and quantization techniques to achieve ultra-low-latency inference (sub-10ms) required for deployment on specialized, resource-constrained edge compute hardware.
• Work directly with forensic data scientists to conceptualize and develop tooling to generate high-fidelity synthetic training scenarios to effectively address data sparsity for rare, critical threat events.
• Oversee the model experimentation, versioning, quality assurance (QA), and transition process into the MLOps pipeline maintained by the DevSecOps team.
• Manage multiple, concurrent AI research and development assignments, providing technical guidance, code review, and mentorship to junior engineers within the AI/ML Squad.
Qualifications:
Required:
• A minimum of 7+ years of progressive experience in Machine Learning, AI research, or applied data science.
• At least 3+ years dedicated experience in the fields of Computer Vision, Object Detection/Tracking, or Multi-Sensor Fusion.
• Expert-level proficiency in Python and deep learning frameworks: PyTorch (preferred) or TensorFlow.
• Demonstrated practical experience utilizing specific detection methodologies (e.g., YOLO family, Faster R-CNN) and/or classical tracking methods (e.g., Kalman Filtering).
• Proficiency in containerization technologies, specifically Docker, for reproducible development and deployment environments.
• Experience with forensic data analysis, data labeling processes, and generating synthetic data for specialized training use cases.
• The candidate shall have a Master's or PhD in Computer Science, AI, Mathematics, or a related quantitative field.
• Must be eligible for a U.S. Government TS/SCI Clearance.
Company:
Our company works with clients to achieve their tactical and strategic goals by unifying sustainable technology solutions which reduce costs, decrease cycle times, and seamlessly manage processes throughout the enterprise. Founded in , the company is headquartered in Washington, USA, with a team of 2-10 employees. The company is currently Early Stage.