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# AI/ML Engineer (Computer Vision & Robotics)

- **Company:** LATENT RISE AI LLC
- **Location:** United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Computer Vision, Automation of Tests, Nvidia CUDA, Continuous Integration, Python (Programming Language), Object Detection, Inference Optimization, Tensorflow, SONAR (Symantec), Pytorch, Deep Learning, Agentic-AI, Low Latency, Machine Learning Operations, TensorRT, Streamlit Framework, Docker
- **Published:** October 24, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=f30a05416822de0e

## About the Role

We are seeking an AI/ML Engineer with a strong background in computer vision and robotics. In this role, you will be responsible for building, optimizing, and deploying production-grade machine learning systems directly onto edge hardware. You will sit at the intersection of deep learning and robotics, ensuring that our real-time detection models operate with ultra-low latency during high-speed field operations.

If you are obsessed with inference optimization, edge deployments, and making robots smarter, we want to hear from you., * Technical depth in ML/AI with a preference for computer vision and robotics. Preference on experience in modality including EO/IR, Acoustic / SONAR, RF / SAR.

 * Proven contributions, whether in industry or academia, that moved innovative ideas closer to product. 3-5 years industry experience
 * Hands-on execution: the ability to design, build, and ship, not just theorize.
 * Collaborative independence: you're comfortable making autonomous progress, but you thrive in a team environment.
 * Growth mindset: curiosity, adaptability, and willingness to learn new approaches and tools.
 * Are fluent in Python and modern ML frameworks like PyTorch; familiarity with agentic AI frameworks is a bonus.
 * Know your way around CI/CD, automated testing, and documentation, and care about building robust systems.
 * Have some familiarity with data science front-end/UI workflows to support quick demonstrations (streamlit, dash, gradio).
 * Have a track record of driving innovation from research or prototypes into production ready features or products

## Description

* Model Development: Design, train, and deploy deep learning models for computer vision using PyTorch, focusing on real-time object detection and spatial awareness.
 * Inference Optimization: Maximize model inference speed and guarantee low-latency performance on edge hardware utilizing CUDA and TensorRT.
 * Robotics Integration: Seamlessly integrate advanced computer vision models for perception and navigation for robots, drones, unmanned systems, swarms, etc.
 * Edge Deployment: Manage, scale, and maintain containerized edge deployments across distributed hardware using Docker and Kubernetes.
 * Performance Engineering: Drive automated data insights and high-performance edge computing initiatives to deliver measurable accuracy gains and operational efficiency in complex, high-speed field environments.