Senior Computer Vision Engineer (AI)

Location: San Carlos, United States; on-site

Company

Develops solar-powered, AI-assisted cameras that automate traffic-law enforcement and improve road safety.

What you will do

• Develop and improve object-detection and multi-object-tracking models for vehicles, pedestrians, and other road users.
• Own data strategy, including sampling, labeling, dataset versioning, hard-negative mining, class-imbalance management, and edge-case analysis.
• Design rigorous experiments and ablations, and validate improvements on deployed and field-collected data.
• Build reproducible training pipelines with experiment tracking, configuration management, artifact lineage, model registries, metric dashboards, and automated hyperparameter search.
• Define evaluation methods covering precision and recall trade-offs, scenario slices, calibration, and tracking quality.
• Collaborate with embedded engineers on edge deployment while balancing accuracy, latency, memory, and power constraints; lead design reviews and mentor engineers.

Requirements

• 7+ years of experience in machine learning or computer vision, with production model delivery experience.
• Hands-on experience with object detection, multi-object tracking, modern architectures, data augmentation, and evaluation methods.
• Strong understanding of class imbalance, overfitting, dataset leakage, label noise, domain shift, model calibration, and statistically sound validation.
• Experience building reproducible training infrastructure with distributed training, hyperparameter search, metric comparison, and model lineage.
• Strong Python and PyTorch skills, plus experience with large image and video datasets.
• Demonstrated technical leadership across ambiguous, cross-functional projects with clear communication and strong ownership.

Nice to have

• Experience in traffic, automotive, robotics, surveillance, or video analytics.
• 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 dataset-quality tooling.
• Experience deploying vision models on NVIDIA Jetson, Qualcomm Snapdragon, or other edge accelerators.

Culture & Benefits

• Work on computer vision directly connected to road safety and saving lives.
• Small, experienced team where senior engineers have meaningful technical influence.
• Fast-moving startup environment with meaningful ownership.
• Competitive compensation and early-stage equity.
• Series A funding of $22M led by Bain Capital.