ForwardDeployedEngineer(MachineLearning)

Our client is building vision agents for large venues such as hotels and casinos— powering real-time video analytics and intelligent surveillance across hundreds of camera streams. Our systems run on-prem in some of the largest resorts in Las Vegas, and many more in the pipeline. They’re a highly technical team shipping deep tech into one of the most operationally demanding and dynamic environments. **The Role** We’re looking for a **Forward Deployed ML Engineer** who blends strong technical ML/CV ability with comfort deploying systems in the field. You will own our real-time vision pipelines end-to-end and be the technical face of the client's inside casinos. This role is **not** a back-office research job. **You will:** * Ship models into production * Debug production pipelines at client sites * Build new ML features ranging from classical ML, computer vision and LLMs * Work hands-on with GPU servers & multi-camera systems * Collaborate with customer surveillance teams and distribution partners If you love solving real-world problems in messy environments, this is your role. **What You’ll Do** * Train, tune, and update/deploy deep learning models at client sites * Maintain low-latency inference pipelines on-premise using PyTorch, ONNX, and TensorRT and Triton. * Build training data processing pipelines, QA/QC labeling and coordinate work with our labelling teams * Work closely with customers and with the product manager to experiment and ship new features **Requirements** * **2-3 years of experience in machine learning** with strong knowledge about not just deep learning but also classical ML (You’re an ML engineer first — someone who can train models, tune them, debug them in the wild, and build the software around them to make them production-ready.). * Strong skills in **Linux, Docker, and shipping models** as services. * Comfortable working in live production environments with minimal supervision. * A **startup mindset** — resourceful, adaptable, and excited t