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Remote Senior Machine Learning Engineer Jobs in Detroit, MI

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 ...

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 ...

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 ...

Machine Learning Engineer

Detroit, MI · On-site +1

$107K - $241K/yr

As a Machine Learning Engineer, you will design and develop the platforms and frameworks that facilitate automated data-driven decision-making, gather data, and determine statistical algorithms and ...

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

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 ...

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Showing results 1-20

Remote Senior Machine Learning Engineer information

See Detroit, MI salary details

$74.7K

$141.9K

$190.1K

How much do remote senior machine learning engineer jobs pay per year?

As of Jul 4, 2026, the average yearly pay for remote senior machine learning engineer in Detroit, MI is $141,853.00, according to ZipRecruiter salary data. Most workers in this role earn between $121,300.00 and $159,900.00 per year, depending on experience, location, and employer.

How do Remote Senior Machine Learning Engineers typically collaborate with cross-functional teams despite working remotely?

Remote Senior Machine Learning Engineers often work closely with data scientists, product managers, and software engineers using digital collaboration tools such as Slack, Jira, and video conferencing platforms. Regular virtual meetings and code reviews are standard practices to ensure alignment on project goals and to facilitate knowledge sharing. Clear communication, proactive documentation, and adaptability to different time zones are key to effective teamwork in a remote environment. This structure allows for flexibility while maintaining strong collaboration and project momentum.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data modeling, and working at large tech companies or in specialized industries can earn salaries approaching or exceeding $500,000 annually, often including bonuses and stock options. Such compensation typically requires a strong educational background, a track record of impactful projects, and expertise in tools like TensorFlow or PyTorch.

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

AspectRemote Senior Machine Learning EngineerRemote Data Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models, collaborates with engineering teamsAnalyzes data, builds statistical models, provides insights
Employer & Industry UsageTech companies, startups, AI-focused firmsResearch institutions, tech companies, finance, healthcare

Remote Senior Machine Learning Engineers focus on designing, building, and deploying ML models, often working closely with engineering teams. Data Scientists analyze data and develop insights, but may not always deploy models. Both roles require strong technical skills and are highly sought after in tech industries, but their core responsibilities differ.

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

To thrive as a Remote Senior Machine Learning Engineer, you need deep expertise in machine learning algorithms, statistical analysis, and strong programming skills (often in Python or similar languages), typically supported by a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (AWS, GCP, or Azure), and experience with data engineering pipelines are commonly required, along with certifications like TensorFlow Developer or AWS Machine Learning Specialty. Excellent problem-solving, communication, and self-management skills help you collaborate remotely, lead projects, and explain complex models to stakeholders. These skills and qualities are vital for building scalable ML solutions, ensuring effective teamwork across distributed environments, and delivering impactful results.

What does a Remote Senior Machine Learning Engineer do?

A Remote Senior Machine Learning Engineer designs, develops, and deploys machine learning models and systems while working from a location outside the traditional office. They collaborate with cross-functional teams, analyze large datasets, build scalable algorithms, and often mentor junior engineers. Their work helps organizations automate processes, gain insights, and improve products or services using data-driven approaches. Senior engineers are also responsible for ensuring model performance, reliability, and integration into production environments. Working remotely, they use various communication and collaboration tools to stay connected with their team.

What engineers make $300,000 a year?

Senior machine learning engineers can earn $300,000 or more annually, especially with extensive experience, advanced skills in deep learning and data modeling, and work at large tech companies or in specialized industries. Compensation often includes base salary, bonuses, and stock options, particularly in high-demand markets.

Will MLE be replaced by AI?

As a Senior Machine Learning Engineer, the role involves designing, developing, and maintaining AI systems, which currently require human expertise. While AI tools can automate certain tasks, the need for skilled professionals to interpret data, ensure ethical use, and improve models remains essential. AI is more likely to augment rather than replace the responsibilities of MLEs in the foreseeable future.

What engineers make $200,000 a year?

Senior machine learning engineers often earn $200,000 or more annually, especially with extensive experience, advanced skills in deep learning and data modeling, and proficiency with tools like TensorFlow or PyTorch. Compensation can vary based on industry, location, and company size, with some roles in tech giants or specialized fields reaching or exceeding this level.
What are popular job titles related to Remote Senior Machine Learning Engineer jobs in Detroit, MI? For Remote Senior Machine Learning Engineer jobs in Detroit, MI, the most frequently searched job titles are:
Infographic showing various Remote Senior Machine Learning Engineer job openings in Detroit, MI as of June 2026, with employment types broken down into 98% Full Time, and 2% Contract. Highlights an 100% Remote job distribution, with an average salary of $141,853 per year, or $68.2 per hour.
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 9 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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