Blue River Technology

HQ
Santa Clara
Total Offices: 2
182 Total Employees
Year Founded: 2011

Blue River Technology Benefits Overview

Compensation + Benefits

Offers 401(K)

Offers life insurance

Offers accidental death & dismemberment insurance

Offers disability insurance

Offers occupational accident insurance

Provides adoption assistance

Offers generous parental leave

Provides family medical leave

Offers company equity

Offers employee discounts

Offers performance bonuses

Offers dental insurance

Offers vision insurance

Offers Health Savings Account (HSA)

Offers health insurance

Offers mental health benefits

Company Culture

Provides commuter benefits

Provides a mobile phone discount

Provides free snacks and drinks

Offers a remote work program

Offers diversity-based Employee Resource Groups

Work-Life Balance + Wellbeing

Offers generous PTO

Provides paid sick days

Provides military leave

Provides paid holidays

Provides bereavement leave

Offers unpaid extended leave

Offers an Employee Assistance Program (EAP)

Career Growth + Development

Provides tuition assistance

Artificial Intelligence • Software
Lead strategy and roadmaps for platform offerings that support robotics and autonomous systems. Drive customer discovery, define requirements and metrics, coordinate cross-functional execution, ensure production readiness, and lead adoption, rollout, and stakeholder communication for platform capabilities.
Artificial Intelligence • Software
Develop, optimize, and deploy production-grade computer vision models (depth, segmentation, tracking) for an autonomous mower. Own model lifecycle from data collection and synthetic-data strategies through training, edge optimization (quantization, mixed precision), and embedded NVIDIA GPU deployment. Integrate perception with robotics stack, analyze field failure cases, and continuously improve robustness for challenging outdoor conditions.
Artificial Intelligence • Software
Support See & Spray CVML team by running reproducible experiments, implementing and evaluating CV and ML models (CNNs to transformer-based), improving evaluation pipelines, debugging models, and applying data-centric AI practices to drive product performance.