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Remote Unique Learning System Jobs in Michigan (NOW HIRING)

Canopy

Senior Machine Learning Engineer

Detroit, MI · On-site +1

$126K - $180K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Establish and refine best practices in our ML system architecture, CI/CD pipelines for ML, and ... Proficiency in Unix-based environments (Linux, macOS) including working with remote servers and ...

Danaher

DBSL, Digital (U.S.A. Remote with 50% Travel)

Detroit, MI · On-site +1

$115K - $155K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... unique viewpoint matter. And by harnessing Danaher's system of continuous improvement, you help ... At IDT, you'll be part of a culture rooted in continuous learning and improvement-where your growth ...

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Remote Unique Learning System information

What is a remote Unique Learning System specialist?

A Remote Unique Learning System specialist is an educator or support professional who uses the Unique Learning System (ULS), an online curriculum specifically designed for students with special needs, to teach or assist students remotely. They adapt lessons, provide instructional support, and monitor student progress using the ULS platform from a remote location. This role often involves collaborating with other educators, supporting families, and ensuring that students receive individualized instruction that meets their learning goals, all through virtual tools.

What are the key skills and qualifications needed to thrive as a remote Unique Learning System specialist?

To thrive as a Remote Unique Learning System Specialist, you need a solid background in special education, instructional design, and familiarity with curriculum adaptation, typically supported by a degree in education or a related field. Expertise in using the Unique Learning System platform, as well as proficiency with virtual classroom tools and assistive technologies, is essential. Strong communication, patience, and problem-solving skills help in effectively supporting students, teachers, and parents remotely. These skills are crucial for delivering personalized, accessible educational experiences and ensuring student success in a virtual learning environment.

What are some common challenges faced when working remotely as an educator using the Unique Learning System, and how can they be managed?

Educators using the Unique Learning System (ULS) remotely often face challenges like maintaining student engagement, adapting lesson plans for virtual delivery, and ensuring accessibility for diverse learners. To overcome these, it's helpful to utilize ULS’s interactive digital resources, set clear communication channels with students and caregivers, and regularly collaborate with support staff and therapists. Scheduling consistent check-ins and leveraging ULS’s progress monitoring tools also ensures that students' needs are met effectively, even from a distance.

What is the difference between Remote Unique Learning System vs Remote Special Education Teacher?

AspectRemote Unique Learning SystemRemote Special Education Teacher
Required CredentialsSpecialized training in learning systems, certifications in educational technologyState teaching certification, special education credentials
Work EnvironmentOnline platform, remote, often project-basedRemote classroom, virtual teaching via video conferencing
Employer & Industry UsageEdTech companies, online learning providersSchool districts, educational institutions
Common Search & ComparisonYesYes

The Remote Unique Learning System focuses on implementing specialized educational technology solutions, often within online platforms, requiring tech-specific certifications. In contrast, a Remote Special Education Teacher provides direct instruction and support to students with disabilities, typically holding teaching credentials. Both roles are remote but differ in credentials, work environment, and industry usage, catering to different aspects of education.

What are the most commonly searched types of Unique Learning System jobs in Michigan?

The most popular types of Unique Learning System jobs in Michigan are:

What are popular job titles related to Remote Unique Learning System jobs in Michigan?

For Remote Unique Learning System jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Remote Unique Learning System jobs in Michigan look for?

The top searched job categories for Remote Unique Learning System jobs in Michigan are:

What cities in Michigan are hiring for Remote Unique Learning System jobs?

Cities in Michigan with the most Remote Unique Learning System job openings:

Remote Unique Learning System jobs near you
Infographic showing various Remote Unique Learning System job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 14% Part Time, 2% Temporary, 3% Contract, and 1% Nights. Highlights an 91% Physical, 3% Hybrid, and 6% Remote job distribution.

Senior Machine Learning Engineer

Canopy

Detroit, MI • On-site, Remote

$126K - $180K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 25 days ago

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Job 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.

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