Remote-Ready Edge AI/ML Engineer – CV & Robotics

Latent AI; Sterling (VA); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Health benefits

Vision benefits

Dental benefits

401(k) plan

Job summary

Latent AI is seeking an AI/ML Engineer to advance edge computing and robotics with real-time computer vision. You will design, train, and deploy production-grade models on edge hardware using PyTorch, CUDA, and TensorRT.

You will work across robotics systems, drones, and autonomous platforms, building scalable, containerized deployments with Docker and Kubernetes in a remote/hybrid setup in the United States (NJ or DC preferred).

Qualifications

• Technical depth in ML/AI with a preference for computer vision and robotics.
• 3-5 years industry experience.
• Hands-on execution: design, build, and ship, not just theorize.
• Fluent in Python and 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.
• Familiar with data science front-end/UI workflows (Streamlit, Dash, Gradio).

Responsibilities

• Model Development: Design, train, and deploy deep learning models for computer vision using PyTorch.
• Inference Optimization: Maximize model inference speed on edge hardware using CUDA and TensorRT.
• Robotics Integration: Integrate computer vision models for perception and navigation across robots, drones, unmanned systems, swarms.
• Edge Deployment: Manage, scale, and maintain containerized edge deployments across distributed hardware using Docker and Kubernetes.
• Performance Engineering: Deliver measurable accuracy gains and efficiency in high-speed field environments.

Skills

Python

PyTorch

Computer vision

Robotics

CUDA

TensorRT

CI/CD

Tools

Docker

Kubernetes

Streamlit

Dash

Gradio

Job description

Latent AI is seeking an AI/ML Engineer to advance edge computing and robotics with real-time computer vision. You will design, train, and deploy production-grade models on edge hardware using PyTorch, CUDA, and TensorRT.

You will work across robotics systems, drones, and autonomous platforms, building scalable, containerized deployments with Docker and Kubernetes in a remote/hybrid setup in the United States (NJ or DC preferred).