Forward Deployed Engineer (Machine Learning)
About The Position
EagleSight 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 with many more in the pipeline. We’re a highly technical team shipping deep tech into one of the most operationally demanding and dynamic environments. 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 EagleSight inside casinos. This role is not a back-office research job. If you love solving real-world problems in messy environments, this is your role.
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 Haves
- 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.
Responsibilities
- 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
- 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.
Benefits
- Ownership over real infrastructure
- Autonomy to ship fast
- Chance to grow along with a team that has gained strong traction in a short period of time.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
