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Senior Tesla Machine Learning Engineer Jobs in Canton, MI

Wayve

Machine Learning Engineer, App SW

Detroit, MI · Hybrid

$283K - $381K/yr

Mentor senior engineers and shape the long-term technical direction across Autonomy. About you: In order to set you up for success as a Machine Learning Engineer at Wayve, we're looking for the ...

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 ...

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Senior Tesla Machine Learning Engineer information

See Canton, MI salary details

$55.1K

$117.3K

$170.1K

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

As of Aug 7, 2026, the average yearly pay for senior tesla machine learning engineer in Canton, MI is $117,287.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,800.00 and $133,000.00 per year, depending on experience, location, and employer.

How does a senior Tesla machine learning engineer typically collaborate with cross-functional teams?

As a Senior Machine Learning Engineer at Tesla, you will frequently work alongside software developers, data scientists, product managers, and hardware engineers. Collaboration is highly cross-functional, with regular meetings to align on project goals, data requirements, and model deployment strategies. You may be involved in translating business objectives into machine learning solutions, sharing insights with non-technical stakeholders, and refining algorithms based on feedback from various departments. This collaborative environment fosters innovation and ensures that machine learning models are well-integrated into Tesla's products and systems.

What are the key skills and qualifications needed to thrive as a senior Tesla machine learning engineer?

To thrive as a Senior Tesla Machine Learning Engineer, you need deep expertise in machine learning algorithms, strong programming skills in Python or C++, and a proven track record in deploying models at scale, often supported by an advanced degree in computer science or a related field. Familiarity with frameworks such as TensorFlow or PyTorch, experience working with large datasets, and cloud computing platforms are typically required, as well as knowledge of Tesla's proprietary systems. Exceptional problem-solving, collaboration, and communication skills distinguish top performers in this role. These abilities are crucial for developing advanced AI solutions that power Tesla's autonomous systems and for driving innovation in a highly competitive, fast-evolving environment.

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

AspectSenior Tesla Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, EE, or related; experience in ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops ML models for autonomous vehicles, energy, and manufacturingAnalyzes data to extract insights, supports product and business decisions
Employer & Industry UsageTesla, automotive, energy, AI projectsVarious industries including tech, finance, healthcare

While both roles involve working with data and algorithms, the Senior Tesla Machine Learning Engineer focuses on developing and deploying machine learning models for Tesla's products, especially autonomous systems. In contrast, a Data Scientist primarily analyzes data to inform business decisions across various industries. The ML Engineer role requires deeper expertise in machine learning frameworks and deployment, whereas Data Scientists focus more on statistical analysis and data visualization.

What does a senior Tesla machine learning engineer do?

A Senior Tesla Machine Learning Engineer leads the development and deployment of advanced machine learning models to improve Tesla’s products, such as Autopilot, Full Self-Driving, and manufacturing optimization. They collaborate with multidisciplinary teams to collect data, design algorithms, and ensure models are robust and scalable. In this role, engineers are expected to mentor junior staff, drive research initiatives, and help translate cutting-edge AI advancements into real-world Tesla applications.
What are popular job titles related to Senior Tesla Machine Learning Engineer jobs in Canton, MI? For Senior Tesla Machine Learning Engineer jobs in Canton, MI, the most frequently searched job titles are:
Senior Tesla Machine Learning Engineer jobs near you
Infographic showing various Senior Tesla Machine Learning Engineer job openings in Canton, MI as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $117,287 per year, or $56.4 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 17 hours 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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