Senior Machine Learning Engineer
About the job
- At least 5 years of professional experience developing and implementing machine learning for perception systems, with expertise in at least one of RADAR, camera, or LiDAR.
- Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field.
- Expertise in Python and extensive experience with at least one deep learning framework, such as PyTorch or TensorFlow.
- Proven ability to develop production-grade machine-learning applications for training, evaluation, and inference on large-scale datasets.
- Experience creating C/C++ applications using modern language features and build systems, preferably to port machine-learning inference applications from Python to edge devices or embedded systems.
- White-box understanding of classical machine-learning algorithms, including support vector machines, hidden Markov models, and decision trees, and modern neural network models and architectures, including convolutional neural networks and transformers, with significant experience applying them to perception systems.
- Experience implementing and applying dynamic object tracking.
- Proficiency in Unix-based environments, including Linux and macOS, and working with remote servers and services, virtual computers, and clusters.
- Proficiency in signal-processing techniques such as time- and frequency-domain processing, Fourier transforms, filtering, and noise reduction.
- Contribute to the design, development, and deployment of robust machine-learning models for production use in real-world security applications.
- Develop across the full machine-learning lifecycle, from problem definition to data-pipeline design, model development, validation, deployment, and monitoring.
- Establish and refine best practices in machine-learning system architecture, continuous integration and continuous delivery pipelines for machine learning, and reproducible research methodologies.
- Collaborate with product managers, data engineers, and MLOps teams to ensure seamless model integration and delivery.
- Perform advanced exploratory data analysis on large-scale sensory datasets, including image, audio, radar, and accelerometer data, to derive insights and guide modeling strategies.
- Stay current with industry advancements in machine learning, AI sensing, and signal processing, and incorporate innovations into the technology stack.
- Mentor and guide junior engineers and contribute to the hiring process and technical reviews.
- Shape the AI roadmap and influence system architecture decisions.
- Experience implementing sensor fusion.
- Experience deploying models to edge hardware, including experience with PyTorch and ONNX and model-compression techniques such as quantization and pruning.
- Experience using cloud-computing platforms such as AWS or GCP.
- Experience with MATLAB for algorithm prototyping and research.
- Experience with Docker or containerization.
- Residence within the Detroit area or nearby, with the ability to work in a hybrid environment and regularly commute to the Detroit office as needed.
About the company
Canopy Vehicle Security provides protection for vehicles by combining patented AI-powered security technology with a human monitoring layer. Its system analyzes signals and vehicle behavior to detect potential threats and issues warning alerts before any theft or tampering happens, with security specialists actively monitoring and ready to intervene. 1) What it does: Prevents vehicle theft and tampering by delivering proactive alerts and security monitoring. 2) How it works: A hardware-and-software security system uses patented AI to monitor signals and activity; when a risk is detected, alerts are sent to the owner and to security experts who can intervene as needed. 3) How it differs: It pairs advanced AI with an expert monitoring team, adding a proactive human-in-the-loop layer that aims to catch threats before they occur, unlike purely automated or passive systems. 4) Goal: Keep vehicles safer by warning owners ahead of threats and providing immediate, expert response support.
Company Size
51-200
Company Stage
N/A
Total Funding
N/A
Headquarters
Detroit, Michigan
Founded
2022
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Simplify's Take
What believers are saying
- Ford kept Canopy expertise for a next-generation Pickup Cam in 2025.
- Ford Security launched in February 2025, validating demand for vehicle theft protection.
- The 2023 nationwide launch proved Canopy can sell subscription hardware through ecommerce.
What critics are saying
- Ford acquired Canopy in 2025 and discontinued Pickup Cam sales.
- Existing Canopy hardware and app shut down by September 2025, destroying customer trust.
- Ford Security now competes directly, making Canopy a likely absorbed product line.
What makes Canopy Vehicle Security unique
- Ford and ADT launched Canopy in January 2022 with $105 million backing.
- Canopy combines Ford camera hardware with ADT professional monitoring for vehicles.
- Pickup Cam targeted trucks and vans with AI threat detection and live alerts.
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Benefits
- Health Insurance
- Dental Insurance
- Vision Insurance
- Health Savings Account/Flexible Spending Account
- Paid Vacation
- Paid Sick Leave
- Paid Holidays
- Parental Leave
- Disability Insurance
- Life Insurance
- Employee Discounts
- Hybrid Work Options