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Obvio
Obvio
51 – 200 Employees
Artificial IntelligenceGovernmentSaaS
Obvio is an artificial intelligence and SaaS company developing traffic-safety technology for cities and law enforcement agencies. Its context-aware AI helps identify reckless driving and traffic violations, including school-zone infractions, failure to yield, distracted driving, and stop-sign violations. By turning roadway activity into actionable insight, Obvio supports municipal leaders and police departments in educating drivers, enforcing traffic laws, reducing violations, and making streets safer.
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Senior Computer Vision Engineer at Obvio — Hybrid in San Carlos

Lead the development of detection and tracking models for Obvio’s AI-assisted traffic cameras. Improve model performance from data strategy and experimentation through edge deployment in the field.

USUnited StatesCACaliforniaHybridFull-timeSeniorEnglish RequiredComputer Vision EngineerMachine Learning Engineer
PythonPyTorch

Description

  • Build and refine object-detection and multi-object-tracking models for vehicles, pedestrians, and other road users in difficult real-world environments.
  • Own the data strategy behind model quality, from sampling and labeling to dataset versioning, hard-negative mining, class imbalance, edge cases, and feedback from deployed systems.
  • Plan rigorous experiments and ablations, separating real gains from overfitting, data leakage, label noise, and improvements that fail in field deployment.
  • Develop reproducible training systems with experiment tracking, configuration management, artifact lineage, model registries, metric dashboards, and automated hyperparameter optimization.
  • Establish product-focused evaluation methods covering precision-recall trade-offs, class and scenario slices, calibration, and tracking performance.
  • Work with embedded engineers to prepare models for edge deployment while balancing accuracy, latency, memory use, and power consumption.
  • Guide technical direction, lead design reviews, mentor engineers, and strengthen standards for machine learning rigor, reproducibility, and production readiness.

Requirements

  • At least seven years of machine learning or computer vision experience, including a record of shipping and improving production models.
  • Advanced practical expertise in object detection and multi-object tracking, including modern architectures, data augmentation, and evaluation techniques.
  • Strong command of class imbalance, overfitting, dataset leakage, label noise, domain shift, model calibration, and statistically rigorous validation.
  • Experience creating training infrastructure or platforms for reproducible experiments, distributed training, hyperparameter search, metric comparison, and model lineage.
  • Advanced Python and PyTorch proficiency.
  • Hands-on experience working with large image and video datasets.
  • Experience evaluating models against deployed or field-collected data and managing the full cycle from failure discovery to retraining and verified improvement.
  • Proven technical leadership across ambiguous, cross-functional initiatives, supported by clear communication and strong ownership.
  • Experience in traffic, automotive, robotics, surveillance, or another video-analytics field.
  • Experience with re-identification, trajectory modeling, occlusion handling, camera calibration, or multi-camera tracking.
  • Experience with active learning, weak supervision, synthetic data, automated labeling, or tools for improving dataset quality.
  • Experience optimizing and deploying computer vision models on NVIDIA Jetson, Qualcomm Snapdragon, or other edge accelerators.
  • Legal authorization to work in the United States.

Benefits

  • Competitive compensation.
  • Equity in an early-stage company.
  • Meaningful ownership within a fast-moving startup environment.
  • The chance to work with a small, experienced team where senior engineers have substantial technical influence.
  • The opportunity to improve road safety and help save lives through your work.

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