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Senior Reinforcement Learning Jobs in Michigan (NOW HIRING)

Mariana Minerals

Machine Learning Engineer

Ann Arbor, MI · On-site

$120K - $160K/yr

Our internal platform uses the same reinforcement learning toolkits that power self-driving ... senior engineers. * Train control models, track and interpret their performance, and dig into why a ...

Megan soft Inc

Senior AI/ML Engineer

Dearborn Heights, MI · On-site

$96K - $132K/yr

... automation, reinforcement learning, virtual assistants and specialized programming * Research and optimize AI technologies to enhance efficiency and accuracy of data analysis and create more ...

FastTek

Machine Learning Engineer

Dearborn, MI

$105K - $126K/yr

Senior Engineer Exp: Prac. In 2 coding lang. or adv. Prac. in 1 lang.; guides. * 10+ years in IT ... fine-tuning (SFT), reinforcement learning from human feedback (RLHF), and instruction tuning

Mariana Minerals

Sr. Data Engineer

Ann Arbor, MI · On-site

$140K - $180K/yr

As a Senior Data Engineer at Mariana, you'll own a data domain end-to-end-designing the pipelines ... Our internal platform, PlantOS, uses the same reinforcement learning toolkits that power self ...

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Senior Reinforcement Learning information

What are some common challenges faced by Senior Reinforcement Learning professionals when deploying models in real-world environments?

Senior Reinforcement Learning professionals often encounter challenges such as ensuring model robustness when transferring algorithms from simulated to real-world environments, handling limited or noisy data, and managing the computational demands of training complex models. Additionally, safety and interpretability are critical, as real-world deployments can have significant impacts if models behave unpredictably. Close collaboration with domain experts and engineering teams is essential to address these challenges and ensure successful, scalable deployments.

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

To thrive as a Senior Reinforcement Learning Engineer, you need deep expertise in machine learning, reinforcement learning algorithms, and programming languages such as Python, often supported by an advanced degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and RL-specific libraries, as well as experience with high-performance computing and cloud platforms, is typically required. Strong problem-solving abilities, collaboration, and communication skills help distinguish top performers in this role. These skills ensure the development of efficient, robust RL models and effective teamwork on complex AI projects.

What is the difference between Senior Reinforcement Learning vs Data Scientist?

AspectSenior Reinforcement LearningData Scientist
Required CredentialsAdvanced degrees in CS, ML, or related fields; experience with RL frameworksDegree in CS, Statistics, or related; strong analytical skills
Work EnvironmentResearch labs, AI teams, tech companies focusing on ML projectsBusiness analytics, data analysis, and modeling in various industries
Employer & Industry UsageTech firms, AI startups, research institutionsFinance, healthcare, marketing, tech, and more

While both roles require strong analytical skills and technical knowledge, Senior Reinforcement Learning specialists focus on developing RL algorithms and models, often in AI research settings. Data Scientists analyze data to inform business decisions across industries. The roles overlap in data handling and programming but differ in their core focus and application areas.

What does a Senior Reinforcement Learning Engineer do?

A Senior Reinforcement Learning Engineer designs, develops, and implements advanced machine learning algorithms that enable systems to learn optimal behaviors through trial and error. They work on complex problems such as robotics, game AI, recommendation systems, and automated decision-making. In addition to coding and model development, they often lead research initiatives, collaborate with cross-functional teams, and mentor junior engineers. Their role requires deep knowledge of reinforcement learning theory, practical experience with machine learning frameworks, and strong programming skills.
What are the most commonly searched types of Reinforcement Learning jobs in Michigan? The most popular types of Reinforcement Learning jobs in Michigan are:
What are popular job titles related to Senior Reinforcement Learning jobs in Michigan? For Senior Reinforcement Learning jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Senior Reinforcement Learning jobs in Michigan look for? The top searched job categories for Senior Reinforcement Learning jobs in Michigan are:
What cities in Michigan are hiring for Senior Reinforcement Learning jobs? Cities in Michigan with the most Senior Reinforcement Learning job openings:
Senior Reinforcement Learning jobs near you
Senior Machine Learning Engineer - Learned Planning/Reinforcement Learning

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

Posted 19 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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