Summary: Seeking a Forward Deployed ML Engineer to own real-time vision pipelines end-to-end, blending strong ML/CV ability with comfort deploying systems in demanding environments. Highlights: 1. Ship models into production and debug pipelines at client sites 2. Build new ML features across classical ML, computer vision, and LLMs 3. Solve real-world problems in challenging operational environments 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 to work across ML, backend, and DevOps boundaries. **Nice to Have** * Experience with **GStreamer, FFmpeg, or RTSP** (or similar protocol) video pipelines. * Experience with **Triton Server, model optimization using TensorRT** and other deep learning acceleration frameworks. **Benefits** * Work remotely Monday \- Friday, 40 hours a week (no weekends) * Vacation: 10 business days a year * Holidays: 5 National Holidays a year * Company Holidays: 5 Company Holidays a year (Christmas Eve, Christmas Day, New Year's Eve, New Year's Day, Zipdev Day) * Parental Leave * Health Care Reimbursement * Active Lifestyle Reimbursement * Quarterly Home Office Reimbursement * Payroll Deduction Purchase Plans * Longevity Bonus * Continuous Learning Bonus * Access to Training and Professional Development Platforms * Did we mention it's REMOTE?!! One of our core values at Zipdev is "Be authentic." that's why we encourage you to answer the application form in your own words; we are interested in getting to know you, not a digital assistant. Wondering how our remote environment or our payment method work? We've put together some helpful answers in our FAQs at the bottom our our career site. Take a look and let us know if you have any other questions!
Juan García
Indeed · HR
Juan García
Indeed · HR
