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Remote E Learning Jobs in Michigan (NOW HIRING)

Canopy

Senior Machine Learning Engineer

Detroit, MI · On-site +1

$126K - $180K/yr

Proficiency in Unix-based environments (Linux, macOS) including working with remote servers and ... Experience using cloud computing platforms, e.g., AWS or GCP. * Experience with MATLAB for ...

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What are the key skills and qualifications needed to thrive in the Remote E Learning position, and why are they important?

To excel in Remote E Learning roles, you need expertise in instructional design, digital pedagogy, and often a background in education or a related field. Familiarity with Learning Management Systems (LMS) like Moodle or Canvas, e-learning authoring tools such as Articulate or Captivate, and sometimes certifications in online teaching or instructional technology are highly valued. Strong communication, time management, and creative problem-solving are vital soft skills for engaging remote learners and collaborating with virtual teams. These abilities ensure effective curriculum delivery, learner engagement, and smooth project execution in a fully remote environment.

What is a Remote E Learning job?

A Remote E Learning job involves working online to create, manage, or support digital education programs. This can include roles such as instructional design, e-learning development, online teaching, or learning management system (LMS) administration. These jobs allow professionals to develop and deliver educational content without being physically present in a classroom. Many remote e-learning jobs require expertise in digital education tools, online course creation, and virtual communication.

What are some common challenges faced when working in Remote E Learning positions?

One common challenge in Remote E Learning roles is maintaining high levels of engagement and interaction with students who may be geographically dispersed and have varying levels of digital literacy. Adapting course materials and delivery methods to suit a wide range of learning styles can also be demanding, as is troubleshooting technical issues in real time. Collaborating with instructional designers, subject matter experts, and technical support teams usually happens virtually, requiring proactive communication and strong organization skills. However, with effective digital tools and a learner-centered mindset, many professionals find these challenges rewarding opportunities for creativity and innovation.

What are the most commonly searched types of E Learning jobs in Michigan? The most popular types of E Learning jobs in Michigan are:
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What cities in Michigan are hiring for Remote E Learning jobs? Cities in Michigan with the most Remote E Learning job openings:
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Infographic showing various Remote E Learning job openings in Michigan as of June 2026, with employment types broken down into 87% Full Time, 2% Part Time, and 11% Contract. Highlights an 2% In-person, and 98% Remote job distribution.
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Canopy

Detroit, MI • On-site, Remote

$126K - $180K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 26 days ago

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6.7

Company rating: 6.7 out of 10

Based on 148 frontline employees who took The Breakroom Quiz

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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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