Applied ML Engineer — IoT

Best AI Tools Wiki; San Francisco (CA); Hybrid; USD 140,000 - 210,000; Full time

Benefits offered by this job

Equity package

Learning stipend

Wellness budget

Parental leave

Job summary

Samsara is seeking an Applied ML Engineer to develop AI models for IoT and fleet management. You will work on computer vision for dash cameras, predictive maintenance models, and driver safety scoring using sensor data from millions of connected devices.

The role emphasizes building edge-deployed models and leveraging time-series data from extensive sensor networks to improve fleet operations and safety.

Qualifications

• 3+ years of applied ML experience.
• Experience with computer vision for video analysis.
• Skills in Python and TensorFlow/PyTorch.
• Experience deploying models to edge devices.
• Understanding of time-series data and sensor fusion.

Responsibilities

• Develop AI models for IoT and fleet management.
• Work on computer vision for dash cameras.
• Build predictive maintenance models and driver safety scoring using sensor data from millions of devices.

Skills

Computer Vision

IoT

Edge ML

Python

TensorFlow

PyTorch

Time Series

Job description

Samsara is hiring an Applied ML Engineer to develop AI models for IoT and fleet management. You will work on computer vision for dash cameras, predictive maintenance models, and driver safety scoring using sensor data from millions of connected devices.

Requirements

• 3+ years of applied ML experience
• Experience with computer vision for video analysis
• Skills in Python and TensorFlow/PyTorch
• Experience deploying models to edge devices
• Understanding of time-series data and sensor fusion

Nice to Have

• Experience with fleet or transportation technology
• Background in embedded systems or IoT
• Experience with model optimization for edge deployment
• Familiarity with ADAS or driver monitoring systems

• Equity package
• Learning stipend
• Wellness budget
• Parental leave

Skills

Computer Vision IoT Edge ML Python TensorFlow Time Series

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