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Remote Embedded Machine Learning Jobs in Taylor, MI

... devices/embedded systems. * White-box understanding of classical ML algorithms (SVMs, HMMs ... Proficiency in Unix-based environments (Linux, macOS) including working with remote servers and ...

Senior Machine Learning Engineer

Detroit, MI · On-site +1

$126K - $180K/yr

... devices/embedded systems. * White-box understanding of classical ML algorithms (SVMs, HMMs ... Proficiency in Unix-based environments (Linux, macOS) including working with remote servers and ...

Attorney - Remote

Ann Arbor, MI · Remote

$100 - $150/hr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Develop case strategies and motion practice templates that inform machine learning models in legal ...

Attorney - Remote

Warren, MI · Remote

$100 - $150/hr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Develop case strategies and motion practice templates that inform machine learning models in legal ...

Attorney - Remote

Detroit, MI · Remote

$100 - $150/hr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Develop case strategies and motion practice templates that inform machine learning models in legal ...

Lawyer - Remote

Sterling Heights, MI · Remote

$100 - $150/hr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Develop case strategies and motion practice templates that inform machine learning models in legal ...

Lawyer - Remote

Ann Arbor, MI · Remote

$100 - $150/hr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Develop case strategies and motion practice templates that inform machine learning models in legal ...

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Develop case strategies and motion practice templates that inform machine learning models in legal ...

Lawyer - Remote

Warren, MI · Remote

$100 - $150/hr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Develop case strategies and motion practice templates that inform machine learning models in legal ...

Attorney - Remote

Dearborn, MI · Remote

$100 - $150/hr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Develop case strategies and motion practice templates that inform machine learning models in legal ...

Lawyer - Remote

Detroit, MI · Remote

$100 - $150/hr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Develop case strategies and motion practice templates that inform machine learning models in legal ...

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Remote Embedded Machine Learning information

See Taylor, MI salary details

$65K

$142.4K

$161.5K

How much do remote embedded machine learning jobs pay per year?

As of Jun 17, 2026, the average yearly pay for remote embedded machine learning in Taylor, MI is $142,390.00, according to ZipRecruiter salary data. Most workers in this role earn between $122,100.00 and $160,600.00 per year, depending on experience, location, and employer.

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

To thrive as a Remote Embedded Machine Learning Engineer, you need a solid background in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often supported by a degree in computer science, electrical engineering, or related fields. Familiarity with microcontrollers, edge AI frameworks (such as TensorFlow Lite or Edge Impulse), and version control systems is typically required. Strong problem-solving skills, effective communication, and self-motivation are essential soft skills for collaborating remotely and troubleshooting complex issues. These skills ensure successful deployment of intelligent solutions on resource-constrained devices and effective teamwork in distributed environments.

What is a Remote Embedded Machine Learning Engineer?

A Remote Embedded Machine Learning Engineer is a professional who develops and deploys machine learning models on embedded systems like microcontrollers, IoT devices, and edge hardware, all while working remotely. Their work involves optimizing algorithms to run efficiently on devices with limited computing power, memory, and battery life. These engineers typically use frameworks such as TensorFlow Lite or TinyML to design intelligent features that operate directly on hardware, enabling real-time decision-making without relying heavily on cloud connectivity. They collaborate with cross-functional teams and often troubleshoot both software and hardware issues from a remote location.

What is the difference between Remote Embedded Machine Learning vs Remote Data Scientist?

AspectRemote Embedded Machine LearningRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Electrical Engineering, or related fields; experience with embedded systems and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in data analysis and ML algorithms
Work EnvironmentEmbedded hardware devices, IoT systems, real-time processing environmentsCloud platforms, data analysis labs, remote offices
Employer & Industry UsageTech companies, IoT device manufacturers, automotive, roboticsFinance, healthcare, marketing, tech firms

Remote Embedded Machine Learning specialists focus on integrating ML models into embedded hardware for real-time applications, often working with IoT and robotics. In contrast, Remote Data Scientists analyze large datasets to extract insights, primarily working in cloud or office environments. Both roles require strong analytical skills but differ in technical focus and work settings.

What are some common challenges faced by Remote Embedded Machine Learning Engineers, and how can they be addressed?

Remote Embedded Machine Learning Engineers often encounter challenges related to hardware access, debugging embedded devices remotely, and collaborating with cross-functional teams across time zones. To address these, it's important to set up robust remote development environments, use simulation tools when physical hardware isn't available, and establish clear communication channels for effective teamwork. Regular virtual meetings and detailed documentation also help ensure alignment and smooth progress, despite the remote nature of the work.
What job categories do people searching Remote Embedded Machine Learning jobs in Taylor, MI look for? The top searched job categories for Remote Embedded Machine Learning jobs in Taylor, MI are:
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Canopy

Detroit, MI • Remote

$126K - $180K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 21 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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