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Machine Learning Engineer Jobs in South Lyon, MI

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

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 41-60

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in South Lyon, MI

Machine Learning Engineer information

See South Lyon, MI salary details

$29.4K

$120.3K

$180.8K

How much do machine learning engineer jobs pay per year?

As of Aug 14, 2026, the average yearly pay for machine learning engineer in South Lyon, MI is $120,310.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,800.00 and $144,800.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

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.

More about Machine Learning Engineer jobs

What job categories do people searching Machine Learning Engineer jobs in South Lyon, MI look for?

The top searched job categories for Machine Learning Engineer jobs in South Lyon, MI are:

What cities near South Lyon, MI are hiring for Machine Learning Engineer jobs?

Cities near South Lyon, MI with the most Machine Learning Engineer job openings:

Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in South Lyon, MI as of August 2026, with employment types broken down into 79% Full Time, and 21% Contract. Highlights an 100% In-person job distribution, with an average salary of $120,310 per year, or $57.8 per hour.

Senior Machine Learning Engineer - Learned Planning/Reinforcement Learning

Torc Robotics

Ann Arbor, MI • On-site, Remote

$102K - $140K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 8 days ago

Job description

About the Company
At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business.
A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight.
Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.
Meet the Team
As a Senior Machine Learning Engineer - Learned Planner / Reinforcement Learning, you will develop and deploy machine learning models that drive decision-making for autonomous trucks. Working closely with teams across perception, prediction, planning, and safety, you will build learned behavior systems that enable safe, efficient, and human-like driving in real-world freight environments.
This role focuses on owning model development and delivery for scoped problem areas, contributing to architecture decisions, and driving improvements in model performance, reliability, and iteration speed within the autonomy stack.
What You'll Do
  • Design, develop, and deploy learned behavior models using approaches such as reinforcement learning, behavior cloning, and imitation learning
  • Own end-to-end model development for scoped problem areas, from data ingestion and training to evaluation and deployment
  • Write production-quality ML code to support scalable training, evaluation, and inference workflows
  • Analyze model performance, identify failure modes, and iterate to improve robustness and generalization across driving scenarios
  • Contribute to training pipelines, data workflows, and infrastructure, including working with large-scale datasets from simulation, fleet logs, and on-vehicle data
  • Collaborate with simulation, validation, and autonomy teams to test and evaluate learned behavior models across diverse environments
  • Support integration of learned planning models into simulation and validation frameworks, enabling faster iteration and improved coverage
  • Contribute to model architecture discussions and technical decision-making within the team
  • Mentor junior engineers on implementation, experimentation, and best practices

What You'll Need to Succeed
  • Bachelor's degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or related technical field with 6+ years of industry experience, OR Master's degree with 3+ years OR PhD with 1+ years of experience
  • Experience applying reinforcement learning, imitation learning, or sequence modeling to robotics, autonomous systems, or complex control problems
  • Strong programming skills in Python and PyTorch, with experience writing production-quality ML code
  • Experience training, evaluating, and improving models using large-scale datasets and distributed compute environments
  • Solid understanding of ML architectures used in autonomy systems (e.g., transformers, RNNs, graph neural networks, policy networks)
  • Experience debugging model behavior, analyzing performance metrics, and improving model reliability
  • Ability to translate ambiguous problems into structured ML solutions and deliver results independently
  • Experience collaborating cross-functionally to integrate ML models into larger autonomy systems

Bonus Points:
  • Experience in autonomous driving, robotics, or simulation-based training environments
  • Experience with reinforcement learning frameworks or distributed training systems (e.g., Ray)
  • Experience working with simulation environments, scenario generation, or large-scale behavior datasets
  • Familiarity with vehicle dynamics, motion planning, or multi-agent decision-making systems
  • Experience deploying ML models into production or real-world robotics systems
  • Experience with learned planning systems or policy learning in real-world or simulation environments
  • Experience integrating learned behavior models into validation and V&V workflows
  • Background in multi-agent modeling, driver behavior modeling, or long-horizon decision-making systems

Work Location: For this position, we are open to hiring in either the Ann Arbor, MI OR Blacksburg, VA (U.S.) office work locations in a hybrid capacity. We are also open to hiring Remote in the United States
Perks of Being a Full-time Torc'r
Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers:
  • A competitive compensation package that includes a bonus component and stock options
  • 100% paid medical, dental, and vision premiums for full-time employees
  • 401K plan with a 6% employer match
  • Flexibility in schedule and generous paid vacation (available immediately after start date)
  • Company-wide holiday office closures
  • AD+D and Life Insurance

At Torc, we're committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc'rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities.
Even if you don't meet 100% of the qualifications listed for this opportunity, we encourage you to apply.
Our compensation reflects the cost of labor across several geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Torc's total compensation package will also include our corporate bonus and stock option plan. Dependent on the position offered, sign-on payments, relocation, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.
Job ID: 102603
Hiring Range for Job Opening
US Pay Range
$226,400-$271,700 USD

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