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Machine Learning Engineer Jobs in Novi, MI (NOW HIRING)

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 of AI Engineering, you'll contribute to the development of cutting-edge AI solutions to combat ...

AI and Machine Learning Engineer

Detroit, MI

$104K - $125K/yr

Machine Learning And Artificial Intelligence Developer You will be responsible for Machine Learning and Artificial Intelligence application development through its lifecycle, from concept and design ...

In order to set you up for success as a Machine Learning Engineer at Wayve, we're looking for the following skills and experience. Essential * Extensive and proven track record of shipping deep ...

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Machine Learning Engineer information

See Novi, MI salary details

$29.6K

$120.8K

$181.5K

How much do machine learning engineer jobs pay per year?

As of Jun 9, 2026, the average yearly pay for machine learning engineer in Novi, MI is $120,810.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,200.00 and $145,400.00 per year, depending on experience, location, and employer.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What jobs make $3,000 a month without a degree?

A Machine Learning Engineer typically requires a degree, but roles such as data annotator, technical support specialist, or freelance programmer can sometimes earn around $3,000 monthly without a formal degree, especially with relevant skills and experience. These jobs often involve self-taught skills, online certifications, or on-the-job training and may require proficiency in tools like Python or cloud platforms.
What job categories do people searching Machine Learning Engineer jobs in Novi, MI look for? The top searched job categories for Machine Learning Engineer jobs in Novi, MI are:
What cities near Novi, MI are hiring for Machine Learning Engineer jobs? Cities near Novi, MI with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Novi, MI as of June 2026, with employment types broken down into 97% Full Time, 2% Part Time, and 1% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $120,810 per year, or $58.1 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 15 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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