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Hourly Remote Machine Learning Engineer Jobs in Michigan

Canopy

Senior Machine Learning Engineer

Detroit, MI · On-site +1

$126K - $180K/yr

As a Senior Machine Learning Engineer within the AI Squad at Canopy and reporting to the Director ... Proficiency in Unix-based environments (Linux, macOS) including working with remote servers and ...

Autodesk

Senior Machine Learning Test Engineer

Novi, MI · On-site +1

$103K - $134K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East Coast Position Overview As a Senior Machine Learning Test Engineer in the Research Enablement team ...

Varsity Tutors

Machine Learning Tutor

Ann Arbor, MI · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Kalamazoo, MI · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Detroit, MI · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Detroit Defense

AI Engineer

Troy, MI · On-site +1

$78K - $82K/yr

... remote. The AI Engineer plays a pivotal role in advancing Detroit Defense's mission across the ... Build, train, and evaluate machine learning models for classification, prediction, and simulation ...

THOMSON REUTERS

Lead Research Engineer

Ann Arbor, MI · On-site +1

$100K - $132K/yr

... remote teams. * Be an Agile Person:With a strong sense of urgency and a desire to work in a fast ... Experienceintegrating Machine Learning solutionsinto production-grade softwarewith a sound ...

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Hourly Remote Machine Learning Engineer information

What are some common challenges faced by hourly remote machine learning engineers, and how can they be addressed?

Hourly remote machine learning engineers often encounter challenges such as managing time effectively across multiple projects, ensuring clear communication with distributed teams, and accessing necessary data or computing resources remotely. Building strong routines for regular check-ins and using collaborative tools can help maintain alignment with project goals. Additionally, proactively clarifying expectations and deliverables with clients or team leads can minimize misunderstandings and improve productivity in a remote, hourly environment.

What does an Hourly Remote Machine Learning Engineer do?

An Hourly Remote Machine Learning Engineer is a professional who develops and implements machine learning models and algorithms for clients or employers on an hourly contract basis, all while working from a remote location. Their responsibilities typically include data preprocessing, model selection, training, testing, and deployment. They collaborate with teams via online tools, manage their own schedules, and deliver results according to project requirements. This role allows for flexibility and the opportunity to work on diverse projects across different industries.

What are the key skills and qualifications needed to thrive as an Hourly Remote Machine Learning Engineer, and why are they important?

To thrive as an Hourly Remote Machine Learning Engineer, you need strong programming skills (especially in Python), a solid understanding of machine learning algorithms, and experience with data preprocessing, typically supported by a relevant degree or equivalent experience. Familiarity with tools and frameworks such as TensorFlow, PyTorch, scikit-learn, cloud platforms (e.g., AWS, GCP), and version control systems like Git is essential. Excellent time management, self-motivation, and clear communication skills help you collaborate effectively across distributed teams and manage project-based work. These skills and qualities are vital for delivering high-quality results independently, meeting deadlines, and adapting to the dynamic needs of remote projects.
What are the most commonly searched types of Remote Machine Learning Engineer jobs in Michigan? The most popular types of Remote Machine Learning Engineer jobs in Michigan are:
What are popular job titles related to Hourly Remote Machine Learning Engineer jobs in Michigan? For Hourly Remote Machine Learning Engineer jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Hourly Remote Machine Learning Engineer jobs in Michigan look for? The top searched job categories for Hourly Remote Machine Learning Engineer jobs in Michigan are:
Hourly Remote Machine Learning Engineer jobs near you
Infographic showing various Hourly Remote Machine Learning Engineer job openings in Michigan as of June 2026, with employment types broken down into 1% Locum Tenens, 1% As Needed, 38% Full Time, 54% Part Time, 5% Contract, and 1% Nights. Highlights an 38% Physical, 3% Hybrid, and 59% 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 5 days ago

Key responsibilities

  • Contribute to the design, development, and deployment of machine learning models for production use in security applications.

  • Develop within the full machine learning lifecycle, including problem definition, data pipeline design, model development, validation, deployment, and monitoring.

  • Establish and refine best practices in machine learning system architecture, CI/CD pipelines for ML, and reproducible research methodologies.

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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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