Home › Companies › Canopy 7 › Senior Machine Learning Engineer
Senior Machine Learning Engineer
Canopy 7 · Detroit, United States (Remote) · Remote · Active · $126,000–$180,000 / year · Workable
Job facts
| Field | Value |
|---|---|
| Company | Canopy 7 |
| Title | Senior Machine Learning Engineer |
| Normalized title | - |
| Department / team | AI/ML |
| Location | Detroit, United States |
| Work model | Remote / Remote |
| Employment type | Full Time |
| Salary | $126,000–$180,000 / year |
| Status | active |
| ATS provider | Workable |
| Posted / first seen | 2026-01-26 / 2026-05-31 |
| Changed / last seen | 2026-05-31 / 2026-06-06 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Canopy 7. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Workable. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| City jobs | Active postings in Detroit. | Open |
| Department jobs | Active postings in AI/ML. | Open |
| Work model jobs | Active Remote postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Canopy 7 |
| Source | cd73c018-1962-42ee-811f-605eb0640d23 |
| ATS provider | Workable |
Description
Description
As a Senior Machine Learning Engineer within the AI Squad at Canopy and reporting to the Director of AI Engineering, you’ll contribute to the development of cutting edge AI solutions to combat vehicle and content theft. In this senior role, you’ll play a pivotal part in shaping our AI roadmap, mentoring junior engineers, and influencing system architecture decisions. This is a high impact role with visibility across engineering and product leadership.
Responsibilities:
Contribute to the design, development, and deployment of robust machine learning models for production use in real world security applications.
Develop within the full machine learning lifecycle; from problem definition to data pipeline design, model development, validation, deployment, and monitoring.
Establish and refine best practices in our ML system architecture, CI/CD pipelines for ML, and reproducible research methodologies.
Collaborate with cross functional stakeholders including product managers, data engineers, and MLOps teams to ensure seamless model integration and delivery.
Perform advanced exploratory data analysis on large scale sensory datasets (image, audio, radar, accelerometer) to derive insights and guide modeling strategies.
Stay ahead of industry advancements in machine learning, AI sensing, and signal processing, incorporating the latest innovations into Canopy’s technology stack.
Mentor and guide junior engineers and contribute to the hiring process and technical reviews.
Requirements
5+ years of professional experience developing and implementing ML for perception systems with expertise in at least one of either RADAR, camera, or LiDAR.
Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field.
Expertise in Python with extensive experience in at least one deep learning framework (PyTorch or TensorFlow.
Proven ability to develop production grade ML applications for training, evaluation and inference on large scale datasets.
Experience creating C/C++ applications utilizing modern language features and build systems, preferably for porting ML inference applications from Python to edge devices/embedded systems.
White box understanding of classical ML algorithms (SVMs, HMMs, Decision Trees) and modern neural network models and architectures (CNNs, transformers) with significant experience applying them for perception systems.
Experience implementing and applying dynamic object tracking, with experience using sensor fusion as a preference.
Proficiency in Unix based environments (Linux, macOS) including working with remote servers and services, virtual computers and clusters.
Proficiency in signal processing techniques such as time/frequency domain processing (e.g. Fourier Transform), filtering, and noise reduction.
Preferred Qualifications:
Experience in deploying models to edge hardware, including experience with PyTorch and ONNX and model compression techniques, e.g. quantisation and pruning.
Experience using cloud computing platforms, e.g., AWS or GCP.
Experience with MATLAB for algorithm prototyping and research.
Experience with Docker or containerisation.
Reside within the Detroit area or nearby, with the ability to work in a hybrid environment and regularly commute to our Detroit office as needed.
Benefits
Comprehensive medical benefits coverage, dental plans and vision coverage.
Health care and dependent care spending accounts.
Employee and Family Assistance Program (EAP).
Employee discount programs.
Retirement plan with a generous company match.
Generous Paid Time Off, Sick, and Holidays
Family Leave (Maternity, Paternity)
Short and long term disability
Life insurance and accidental death & dismemberment insurance
Compensation Range
Compensation may vary depending on skills and experience.
Base Salary: $126,000 $180,000
Diversity, Equity and Inclusion: At Canopy, we're on a mission to end theft from vehicles and revolutionize vehicle security by building cutting edge technology. We will achieve this by prioritizing individuals and staying attuned to the evolving needs of our people, users, and industry trends. We foster a workplace culture that embraces diversity and authenticity, enabling us to flourish as a team of exceptional individuals working towards a common purpose. We gain a deeper understanding of our users' experiences by continuously improving our skills and expanding our knowledge. A more diverse, equitable, and inclusive Canopy leads to greater innovation and success.
Equal Opportunity: Canopy does not discriminate on the basis of race, sex, color, religion, age, national origin, marital status, disability, veteran status, genetic information, sexual orientation, gender identity or any other reason prohibited by law in provision of employment opportunities and benefits.
Full job record
| Job ID | 3cccccf9f2242bf9a5d92b068c11d49b5ed65f12 |
| Org ID | 52761d27-488b-43ae-bd0b-559fc3d2f2ea |
| Source ID | cd73c018-1962-42ee-811f-605eb0640d23 |
| Board ID | cd73c018-1962-42ee-811f-605eb0640d23 |
| Provider | workable |
| Provider Job Key | D0F326A019 |
| Title | Senior Machine Learning Engineer |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | Detroit, United States (Remote) |
| Department | AI/ML |
| Team | — |
| Employment Type | full_time |
| Workplace Type | remote |
| Remote Policy | remote |
| Country | United States |
| Region | — |
| City | Detroit |
| Salary Raw | Description As a Senior Machine Learning Engineer within the AI Squad at Canopy and reporting to the Director of AI Engineering, you’ll contribute to the development of cutting edge AI solutions to combat vehicle and content theft. In this senior role, you’ll play a pivotal part in shaping our AI roadmap, mentoring junior engineers, and influencing system architecture decisions. This is a high impact role with visibility across engineering and product leadership. Responsibilities: Contribute to the design, development, and deployment of robust machine learning models for production use in real world security applications. Develop within the full machine learning lifecycle; from problem definition to data pipeline design, model development, validation, deployment, and monitoring. Establish and refine best practices in our ML system architecture, CI/CD pipelines for ML, and reproducible research methodologies. Collaborate with cross functional stakeholders including product managers, data engineers, and MLOps teams to ensure seamless model integration and delivery. Perform advanced exploratory data analysis on large scale sensory datasets (image, audio, radar, accelerometer) to derive insights and guide modeling strategies. Stay ahead of industry advancements in machine learning, AI sensing, and signal processing, incorporating the latest innovations into Canopy’s technology stack. Mentor and guide junior engineers and contribute to the hiring process and technical reviews. Requirements 5+ years of professional experience developing and implementing ML for perception systems with expertise in at least one of either RADAR, camera, or LiDAR. Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field. Expertise in Python with extensive experience in at least one deep learning framework (PyTorch or TensorFlow. Proven ability to develop production grade ML applications for training, evaluation and inference on large scale datasets. Experience creating C/C++ applications utilizing modern language features and build systems, preferably for porting ML inference applications from Python to edge devices/embedded systems. White box understanding of classical ML algorithms (SVMs, HMMs, Decision Trees) and modern neural network models and architectures (CNNs, transformers) with significant experience applying them for perception systems. Experience implementing and applying dynamic object tracking, with experience using sensor fusion as a preference. Proficiency in Unix based environments (Linux, macOS) including working with remote servers and services, virtual computers and clusters. Proficiency in signal processing techniques such as time/frequency domain processing (e.g. Fourier Transform), filtering, and noise reduction. Preferred Qualifications: Experience in deploying models to edge hardware, including experience with PyTorch and ONNX and model compression techniques, e.g. quantisation and pruning. Experience using cloud computing platforms, e.g., AWS or GCP. Experience with MATLAB for algorithm prototyping and research. Experience with Docker or containerisation. Reside within the Detroit area or nearby, with the ability to work in a hybrid environment and regularly commute to our Detroit office as needed. Benefits Comprehensive medical benefits coverage, dental plans and vision coverage. Health care and dependent care spending accounts. Employee and Family Assistance Program (EAP). Employee discount programs. Retirement plan with a generous company match. Generous Paid Time Off, Sick, and Holidays Family Leave (Maternity, Paternity) Short and long term disability Life insurance and accidental death & dismemberment insurance Compensation Range Compensation may vary depending on skills and experience. Base Salary: $126,000 $180,000 Diversity, Equity and Inclusion: At Canopy, we're on a mission to end theft from vehicles and revolutionize vehicle security by building cutting edge technology. We will achieve this by prioritizing individuals and staying attuned to the evolving needs of our people, users, and industry trends. We foster a workplace culture that embraces diversity and authenticity, enabling us to flourish as a team of exceptional individuals working towards a common purpose. We gain a deeper understanding of our users' experiences by continuously improving our skills and expanding our knowledge. A more diverse, equitable, and inclusive Canopy leads to greater innovation and success. Equal Opportunity: Canopy does not discriminate on the basis of race, sex, color, religion, age, national origin, marital status, disability, veteran status, genetic information, sexual orientation, gender identity or any other reason prohibited by law in provision of employment opportunities and benefits. |
| Salary Min | 126,000 |
| Salary Max | 180,000 |
| Salary Currency | USD |
| Salary Period | year |
| Source URL | https://apply.workable.com/canopy-7/jobs/view/D0F326A019 |
| Apply URL | https://apply.workable.com/canopy-7/j/D0F326A019/apply |
| First Seen At | 2026-05-31 17:47:30Z |
| Last Seen At | 2026-06-06 13:29:29Z |
| Last Checked At | 2026-06-06 13:29:29Z |
| Last Changed At | 2026-05-31 17:47:30Z |
| Inactive At | — |
| Source Posted At | 2026-01-26 00:00:00Z |
| Source Updated At | — |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=workable/board=canopy-7/date=2026-06-06/2026-06-06T13-29-28-934Z-7aa60c355830594016835b7ed8e2e9700707ab33f57123b90b03c5015cb79c32.json |
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