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Fulltime Reinforcement Learning Phd Jobs in Michigan

Eccalon LLC

AI Expert Robotics - onsite

Detroit, MI

Master's degree or PhD in AI, Robotics, or a related discipline * Experience with ROS / ROS2 and ... Experience with computer vision, deep learning, or reinforcement learning * Familiarity with ...

General Motors

Thermal Systems Researcher

Warren, MI · Hybrid

Advanced (PhD) degree in science/engineering disciplines. New PhD grad up to 1-3 years work ... learning, use of digital twins, reinforcement learning. * Strong background in physicsbased ...

General Motors

Thermal Systems Researcher

Warren, MI · On-site

Advanced (PhD) degree in science/engineering disciplines. New PhD grad up to 1-3 years work ... learning, use of digital twins, reinforcement learning. * Strong background in physics-based ...

Magna

Robotics AI Algorithm- R&D Summer 2026

Troy, MI · On-site

... as Deep Learning, Reinforcement learning, Transformers, Natural Language Processing (NLP ... EDUCATION / EXPERIENCE Current Graduate student preferably in a PhD program or MS program focused ...

Magna

Robotics AI Algorithm- R&D Summer 2026

Troy, MI · On-site

... as Deep Learning, Reinforcement learning, Transformers, Natural Language Processing (NLP ... EDUCATION / EXPERIENCE • Current Graduate student preferably in a PhD program or MS program ...

May Mobility

Director, Data Science

Ann Arbor, MI · On-site

... simulation and synthetic data, reinforcement learning, or large-scale ML platforms. • ... Preferred : • Master's or PhD in Computer Science, Robotics, Statistics, EE, Mathematics, or a ...

May Mobility

Director, Data Science

Ann Arbor, MI · On-site

... simulation and synthetic data, reinforcement learning, or large-scale ML platforms. • ... Preferred : • Master's or PhD in Computer Science, Robotics, Statistics, EE, Mathematics, or a ...

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Fulltime Reinforcement Learning Phd information

What is the difference between Fulltime Reinforcement Learning Phd vs Machine Learning Engineer?

AspectFulltime Reinforcement Learning PhdMachine Learning Engineer
Required CredentialsPhD in Computer Science, AI, or related fieldBachelor's or Master's in CS, AI, or related field
Work EnvironmentResearch-focused, academic or R&D labsIndustry, product development teams
Employer & Industry UsageUniversities, research institutions, tech companiesTech companies, startups, enterprise firms
Common Search & ComparisonYesNo

Fulltime Reinforcement Learning Phds typically focus on research and theoretical development in AI, often working in academic or R&D settings. Machine Learning Engineers apply AI techniques to develop practical applications in industry. While both roles require strong AI knowledge, the Phd emphasizes research, whereas the Engineer emphasizes implementation.

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Cities in Michigan with the most Fulltime Reinforcement Learning Phd job openings:

Fulltime Reinforcement Learning Phd jobs near you

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 13 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 CAD

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