AI/ML Engineer (Computer Vision & Robotics)

Posted Yesterday
Hiring Remotely in United States
Remote
Mid level
Artificial Intelligence • Software
The Role
Develop, optimize, and deploy production-grade computer vision and deep learning models for real-time perception and navigation on edge hardware. Integrate AI systems with robots, drones, unmanned systems, and swarms while optimizing inference with CUDA and TensorRT. Manage containerized deployments using Docker and Kubernetes, contribute to CI/CD and automated testing, and transition research prototypes into reliable production features.
Summary Generated by Built In
Who we are

At Latent AI, we are pushing the boundaries of edge computing and artificial intelligence. We specialize in bringing high-performance, low-latency AI to the edge, enabling real-time decision-making in autonomous systems and robotics. We are looking for a passionate and driven AI/ML Engineer to join our team and help us build the next generation of intelligent, physical AI systems.


Who we're looking for

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.

What you’ll do
  • 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.
    How we decide

    An ideal candidate will be someone with;

    • 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


    Location and Benefits
    • US Citizen requirement due to nature of our projects.
    • Candidates based in NJ or Washington DC preferred, remote/hybrid possible.
    • We offer health, vision & dental benefits, a 401(k) plan.

    Skills Required

    • 3-5 years of industry experience
    • Technical depth in machine learning and artificial intelligence
    • Experience with computer vision and robotics
    • Fluency in Python
    • Experience with PyTorch or modern machine learning frameworks
    • Experience designing, training, and deploying deep learning models
    • Experience optimizing inference with CUDA and TensorRT
    • Experience integrating computer vision models into robotics, drones, unmanned systems, or swarms
    • Experience with Docker and Kubernetes for edge deployments
    • Familiarity with CI/CD, automated testing, and technical documentation
    • Familiarity with Streamlit, Dash, or Gradio
    • Track record of moving research or prototypes into production-ready features or products
    • Familiarity with EO/IR, acoustic or SONAR, RF, or SAR modalities
    • Familiarity with agentic AI frameworks
    • US citizenship
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    The Company
    HQ: Menlo Park, CA
    28 Employees
    Year Founded: 2018

    What We Do

    Latent AI, Inc. is an early stage venture spinout of SRI International, dedicated to building solutions that enable the adaptive edge to transform AI processing. Latent AI is well-funded by industry-leading investors with support from Fortune 500 clients. The Latent AI Efficient Inference Platform (LEIP™) brings AI to the edge by optimizing for compute, energy, and memory without requiring changes to existing AI/ML infrastructure and frameworks. The company is founded by Jags Kandasamy and Sek Chai. They bring decades of combined industry experience and R&D expertise in machine learning AI (lifelong learning), computer vision, embedded systems, IoT applications, and efficient computing.

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