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Senior Reinforcement Learning Jobs in Michigan (NOW HIRING)

Mariana Minerals

Machine Learning Engineer

Ann Arbor, MI · On-site

$120K - $180K/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 ...

Mariana Minerals

Sr. Data Engineer

Ann Arbor, MI · On-site

$140K - $200K/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 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 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 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:

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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

Machine Learning Engineer

Mariana Minerals

Ann Arbor, MI • On-site

Full-time

Re-posted 28 days ago

Job description

Job Summary:
Mariana Minerals is a software-first, vertically integrated minerals company focused on supplying critical minerals for modern energy and technology. They are seeking a Machine Learning Engineer to develop and improve machine learning systems for mineral refining facilities, working with real data to enhance operational efficiency.
Responsibilities:
• Run reinforcement learning experiments in our physically realistic simulators of mineral processing operations, and help turn the results into better controllers.
• Build and refine pieces of our training environments—reward functions, observations, and action logic—with guidance from senior engineers.
• Train control models, track and interpret their performance, and dig into why a model underperforms.
• Help close the gap between simulation and reality by comparing model behavior against real plant data and flagging where the physics diverges.
• Write clean, well-tested code and contribute to the services that put models into production.
• Partner with process and chemistry experts to understand the unit operations you're modeling.
Qualifications:
Required:
• 0–4 years of experience (including internships or research) in machine learning, reinforcement learning, or scientific computing—or a strong recent graduate with demonstrated project depth.
• Solid grounding in machine learning fundamentals, with working knowledge of modern deep learning; exposure to reinforcement learning is a strong plus.
• Proficiency in Python and comfort reading and debugging an existing codebase.
• Curiosity about physical, industrial systems and eagerness to learn chemistry and process engineering from experts who will challenge your assumptions.
• A self-starter who asks good questions, ships, and escalates blockers early.
Company:
Mariana Minerals develops mineral projects using technology to supply critical minerals for energy, AI, and defense applications. Founded in 2024, the company is headquartered in Houston, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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