Senior ML Engineer – Perception & Edge AI (Hybrid)

Canopy Limited; Detroit (MI); Hybrid; USD 126,000 - 180,000; Full time

Benefits offered by this job

Comprehensive medical benefits

Dental and vision plans

Retirement plan with company match

Generous paid time off

Family leave (maternity/paternity)

Disability insurance

Life insurance

Job summary

Canopy is seeking a Senior Machine Learning Engineer within the AI Squad in Detroit. You will shape the AI roadmap, mentor engineers, and influence system architecture for real-world security applications.

Responsibilities include end-to-end ML development, collaboration with cross-functional teams, and advancing ML/AI sensing technologies. Hybrid work with leadership exposure and a strong focus on production-grade systems.

Qualifications

• 5+ years of ML development for perception systems (RADAR, camera or LiDAR).
• Production-grade ML applications for training, evaluation, and inference.
• Experience porting ML inference to edge devices/embedded systems.

Responsibilities

• Design, develop, and deploy ML models for security applications.
• Lead full ML lifecycle: problem definition, data pipelines, training, validation, deployment, monitoring.
• Refine ML system architecture, CI/CD for ML, and reproducible research practices.
• Collaborate with product managers, data engineers, and MLOps teams for integration.
• Perform advanced exploratory data analysis on large-scale sensor data.
• Stay updated with ML and signal processing innovations and apply to Canopy stack.
• Mentor junior engineers and participate in hiring and technical reviews.

Skills

Python programming

PyTorch

TensorFlow

C/C++

Sensor fusion

Linux/Unix

Edge ML deployment

Education

Bachelor's degree in Computer Science, Data Science, or Engineering

Tools

ONNX

Docker

MATLAB

AWS

GCP

Job description

Canopy is seeking a Senior Machine Learning Engineer within the AI Squad in Detroit. You will shape the AI roadmap, mentor engineers, and influence system architecture for real-world security applications.

Responsibilities include end-to-end ML development, collaboration with cross-functional teams, and advancing ML/AI sensing technologies. Hybrid work with leadership exposure and a strong focus on production-grade systems.