Computer Vision/ML Engineer

Job summary

Lead the development and deployment of real-time computer vision models for autonomous healthcare robots on edge devices. Establish MLOps pipelines and optimize the CV stack from research to production.

Job details

The company Norbert is building autonomous robots that deliver healthcare. Our AI sensing platform mounts on mobile robots and does the work of a care team member—rounding on patients, capturing vitals without contact (FDA-cleared for pulse and respiratory rate, more in the pipeline), running assessments, documenting to the EMR, and escalating when something's wrong. Autonomously. We're not building demos. We're deployed in real facilities today, monitoring hundreds of patients daily. We're solving one of healthcare's hardest problems: a global nursing shortage that will hit 40% by 2030. We're a small, international team backed by top-tier VCs, with offices in Brooklyn and Paris. We ship things that matter. The position We are looking for our lead deep learning engineer to spearhead the development of our groundbreaking sensing technology. What you will do: Design, fine-tune, and deploy computer vision models (YOLO, InsightFace, MediaPipe, facial landmark detection, object tracking, pose estimation) for real-time inference on the edge Optimize models for embedded deployment using quantization, pruning, TensorRT, and NVIDIA Triton Build and maintain MLOps pipelines for model training, validation, and performance monitoring Develop video processing pipelines that integrate with both classical signal processing and ML based vital sign extraction Establish engineering best practices and help reduce technical debt as we scale Contribute to the architecture and implementation of the computer vision stack from research to production What we look for: Master's or PhD degree in Machine learning / Computer vision Strong fundamentals: data structures, CV algorithms, and systems programming Strong C++ skills - this is critical for our edge deployment pipeline Solid Python proficiency for ML experimentation and tooling Ability to work independently, solve complex problems, and drive projects to completion 5+ years experience deploying computer vision models to production, ideally on resource-constrained devices Experience with PyTorch and model optimization for edge AI Proven ability to take models from research to production on embedded hardware Nice to haves: Experience with NVIDIA Jetson platform, TensorRT, or Triton Inference Server MLOps experience (experiment tracking, model versioning, performance monitoring) Experience with sensor fusion (RGB, IR, depth cameras) Background in medical devices, regulated environments, or healthcare applications Experience working in fast-moving early-stage environments What we offer: Real impact: your code provides care for patients today High autonomy and technical ownership - you'll shape our computer vision architecture Work at the intersection of cutting-edge AI, edge computing, and healthcare A talented, excellent, diverse and international team Cutting-edge stack: embedded AI, robotics, LLMs, multimodal sensing Talented, international team tackling meaningful problems in remote patient monitoring Competitive salary Transparent, mission-driven culture focused on continuous learning

What you’ll do

Lead the development and deployment of real-time computer vision models for autonomous healthcare robots on edge devices. Establish MLOps pipelines and optimize the CV stack from research to production.

Requirements

Requires a Master's or PhD in ML/CV with over 5 years of experience deploying production models to resource-constrained hardware. Strong proficiency in C++ and Python is critical for the edge deployment pipeline.

Benefits

• Competitive Salary • High Autonomy and Technical Ownership

Listed skills

• Validation · Preferred
• Production · Preferred
• Technical · Preferred
• Training · Preferred
• Machine learning · Preferred
• Pipeline · Preferred
• Development · Preferred
• Time · Preferred
• Performance Monitoring · Preferred
• C++ · Preferred
• Tracking · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Computer Vision
• Deep Learning
• C++
• Python
• PyTorch
• TensorRT
• NVIDIA Triton
• MLOps
• Edge AI
• Object Tracking
• Pose Estimation
• Facial Landmark Detection
• Quantization
• Pruning
• Sensor Fusion
• Embedded Systems

Job areas

• Technology
• Engineering
• Healthcare
• Software
• Science & Research