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Reinforcement Learning Engineer Jobs in Michigan

Senior AI Ops Engineer

Ann Arbor, MI · On-site

$102K - $140K/yr

... and Reinforcement Learning with Human Feedback (RLHF). We encourage you to apply if you're a systems-minded engineer who loves turning research workflows into reliable production-grade pipelines ...

... learning, Reinforcement Learning, Natural Language Processing (NLP), SVM, XGBoost, Random Forest, Decision Trees, Clustering * Data Engineering : Databricks, Hadoop, SQL, Data Pipelines, Data ...

Senior AI Ops Engineer

Ann Arbor, MI · On-site

$102K - $140K/yr

... and Reinforcement Learning with Human Feedback (RLHF). We encourage you to apply if you're a systems-minded engineer who loves turning research workflows into reliable production-grade pipelines ...

Senior AI Ops Engineer

Ann Arbor, MI

$102K - $140K/yr

... and Reinforcement Learning with Human Feedback (RLHF). We encourage you to apply if you're a systems-minded engineer who loves turning research workflows into reliable production-grade pipelines ...

Sr. Data Engineer

Ann Arbor, MI · On-site

$140K - $180K/yr

Our internal platform, PlantOS, uses the same reinforcement learning toolkits that power self ... ML engineers own the features and models built on top of it. The training and monitoring layer is ...

... learning, Reinforcement Learning, Natural Language Processing (NLP), SVM, XGBoost, Random Forest, Decision Trees, Clustering * Data Engineering : Databricks, Hadoop, SQL, Data Pipelines, Data ...

The resource also provides technical oversight to developers in the team that support other ... or reinforcement learning. • Experience with OCR (Optical Character Recognition) Tesseract ...

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Showing results 1-20

Reinforcement Learning Engineer information

See Michigan salary details

$33.1K

$101K

$166.9K

How much do reinforcement learning engineer jobs pay per year?

As of Jun 18, 2026, the average yearly pay for reinforcement learning engineer in Michigan is $100,987.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,300.00 and $132,000.00 per year, depending on experience, location, and employer.

What are Reinforcement Learning Engineers?

Reinforcement Learning Engineers are specialized professionals who design, develop, and implement algorithms based on reinforcement learning, a type of machine learning where agents learn to make decisions by receiving rewards or penalties. They work on building models that enable machines to learn optimal actions through trial and error in complex environments. Their responsibilities often include developing RL architectures, tuning hyperparameters, running simulations, and applying RL methods to real-world problems like robotics, gaming, or recommendation systems. RL Engineers typically have strong backgrounds in computer science, mathematics, and deep learning, along with experience in programming languages like Python and frameworks such as TensorFlow or PyTorch.

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

To thrive as a Reinforcement Learning Engineer, you need a strong background in machine learning, mathematics (especially probability and statistics), and programming languages like Python, often supported by a relevant degree in computer science or engineering. Familiarity with deep learning frameworks (such as TensorFlow or PyTorch), RL libraries (like OpenAI Gym), and cloud computing platforms is typically required. Problem-solving skills, creativity, and effective collaboration help set outstanding engineers apart in this field. These competencies enable the design and deployment of advanced RL solutions that address real-world challenges and drive innovation.

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

One of the main challenges Reinforcement Learning (RL) Engineers face is bridging the gap between simulation and real-world deployment. Models that perform well in controlled environments may struggle with unpredictable data, safety constraints, or limited feedback in production. Additionally, RL algorithms often require significant computational resources and careful tuning to avoid instability. Collaboration with domain experts and software engineers is essential to address these issues and ensure successful integration of RL solutions into existing systems.

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

AspectReinforcement Learning EngineerMachine Learning Engineer
CredentialsBachelor's/Master's in CS, AI, or related; experience with RL frameworksBachelor's/Master's in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on RL applicationsTech companies, data-driven firms, AI departments across industries
Industry UsageSpecialized in RL projects like robotics, game AI, autonomous systemsBroader applications including predictive modeling, NLP, computer vision

Reinforcement Learning Engineers focus on developing algorithms that learn through interactions with environments, often in robotics or gaming. Machine Learning Engineers work on a wider range of models and applications. While both roles require strong programming and math skills, RL Engineers specialize in sequential decision-making, whereas ML Engineers handle diverse data-driven tasks across industries.

What are popular job titles related to Reinforcement Learning Engineer jobs in Michigan? For Reinforcement Learning Engineer jobs in Michigan, the most frequently searched job titles are:
What cities in Michigan are hiring for Reinforcement Learning Engineer jobs? Cities in Michigan with the most Reinforcement Learning Engineer job openings:
Infographic showing various Reinforcement Learning Engineer job openings in Michigan as of June 2026, with employment types broken down into 99% Full Time, and 1% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $100,987 per year, or $48.6 per hour.
Senior AI Ops Engineer

Senior AI Ops Engineer

Kla

Ann Arbor, MI • On-site

$102K - $140K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 22 days ago


Job description

Company Overview

KLA is a global leader in diversified electronics for the semiconductor manufacturing ecosystem. Virtually every electronic device in the world is produced using our technologies. No laptop, smartphone, wearable device, voice-controlled gadget, flexible screen, VR device or smart car would have made it into your hands without us. KLA invents systems and solutions for the manufacturing of wafers and reticles, integrated circuits, packaging, printed circuit boards and flat panel displays. The innovative ideas and devices that are advancing humanity all begin with inspiration, research and development. KLA focuses more than average on innovation and we invest 15% of sales back into R&D. Our expert teams of physicists, engineers, data scientists and problem-solvers work together with the world's leading technology providers to accelerate the delivery of tomorrow's electronic devices. Life here is exciting and our teams thrive on tackling really hard problems. There is never a dull moment with us.

Group/Division

The KLA Services team headquartered in Milpitas, CA is our service organization that consists of Service Sales and Marketing, Spares Supply Chain management, Field Operations, Engineering, Product Training, and Technical Support. The KLA Services organization partners with our field teams and customers in all business sectors to maintain the high performance and productivity of our products through a flexible portfolio of services. Our comprehensive services include: proactive management of tools to identify and improve performance; expertise in optics, image processing and motion control with worldwide service engineers, 24/7 technical support teams and knowledge management systems; and an extensive parts network to ensure worldwide availability of parts.

Job Description/Preferred Qualifications

We seek a highly skilled and passionate Senior AI Ops Engineer to join our team. This role will be pivotal in architecting and delivering the automation layer that enables fast, reproducible, and scalable model development-spanning end-to-end experiment management, model fine-tuning pipelines, and Reinforcement Learning with Human Feedback (RLHF). We encourage you to apply if you're a systems-minded engineer who loves turning research workflows into reliable production-grade pipelines, setting standards, and mentoring others to raise the bar across the organization.

Key Responsibilities:

  • Implement and operate experiment tracking, lineage, and reproducibility standards (datasets, code, configs, artifacts, metrics) using MLflow/W&B or equivalents.
  • Build CI/CD for ML: tests (unit/integration), packaging, reproducibility checks, policy gates, automated deployment and rollback strategies.
  • Design workflow orchestration for large-scale ML jobs (scheduled runs, triggered retrains, parameter sweeps, gated releases) using tools such as Airflow/Kubeflow/Argo or equivalents.
  • Architect, build, and own automated pipelines for model training, fine-tuning (e.g., PEFT/LoRA), evaluation, and promotion across environments (dev staging production).
  • Establish standardized training "recipes" (configs, templates, golden paths) to reduce time-to-first-experiment and improve consistency across teams.
  • Enable and optimize distributed GPU training (throughput, reliability, and cost), including checkpointing, mixed precision, fault tolerance, and spot/preemptible handling where applicable.
  • Develop evaluation harnesses and automated benchmark suites (quality, safety, latency, and cost) with clear, repeatable reporting to compare runs and releases.

Qualifications:

  • Strong proficiency in Python and experience building robust automation frameworks and production-grade services for ML workloads
  • Hands-on experience with experiment tracking and model lifecycle tooling (e.g., MLflow, Weights & Biases) and reproducible ML workflows
  • Practical experience fine-tuning modern deep learning models (e.g., Transformers) and familiarity with parameter-efficient approaches (LoRA/PEFT)
  • Working knowledge of RLHF concepts and pipelines (preference data, reward models, policy optimization) and how to operationalize human-in-the-loop workflows.
  • Experience with containerization (Docker), orchestration (Kubernetes), and operating GPU workloads reliably at scale.
  • Experience with CI/CD, version control (Git), and Infrastructure-as-Code (Terraform/Bicep or equivalent).
  • Excellent problem-solving skills across distributed systems (training jobs, pipelines, compute infrastructure) and strong communication to partner with research and engineering teams.
  • Prior experience in a similar industry and/or operating ML platforms with stringent IP/security requirements is a plus.
  • Bachelor's degree in Computer Science, Software Engineering, or related field
  • 5+ years of experience in MLOps/Platform Engineering/DevOps/ML Engineering (or demonstrated equivalent impact), including owning production systems and leading cross-team initiatives

Minimum Qualifications

  • Master's Level Degree and related work experience of 6 years; OR Bachelor's Level Degree and related work experience of 8 years; OR equivalent work experience

Base Pay Range: $134,800.00 - $229,200.00 AnnuallyPrimary Location: USA-MI-Ann Arbor-KLAKLA's total rewards package for employees may also include participation in performance incentive programs and eligibility for additional benefits including but not limited to: medical, dental, vision, life, and other voluntary benefits, 401(K) including company matching, employee stock purchase program (ESPP), student debt assistance, tuition reimbursement program, development and career growth opportunities and programs, financial planning benefits, wellness benefits including an employee assistance program (EAP), paid time off and paid company holidays, and family care and bonding leave.

Interns are eligible for some of the benefits listed. Our pay ranges are determined by role, level, and location. The range displayed reflects the pay for this position in the primary location identified in this posting. Actual pay depends on several factors, including state minimum pay wage rates, location, job-related skills, experience, and relevant education level or training. We are committed to complying with all applicable federal and state minimum wage requirements where applicable. If applicable, your recruiter can share more about the specific pay range for your preferred location during the hiring process.

KLA is proud to be an Equal Opportunity Employer. We will ensure that qualified individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us attalent.acquisition@kla.com or at +1-408-352-2808 to request accommodation.

Be aware of potentially fraudulent job postings or suspicious recruiting activity by persons that are currently posing as KLA employees. KLA never asks for any financial compensation to be considered for an interview, to become an employee, or for equipment. Further, KLA does not work with any recruiters or third parties who charge such fees either directly or on behalf of KLA. Please ensure that you have searched KLA's Careers website for legitimate job postings. KLA follows a recruiting process that involves multiple interviews in person or on video conferencing with our hiring managers. If you are concerned that a communication, an interview, an offer of employment, or that an employee is not legitimate, please send an email to talent.acquisition@kla.com to confirm the person you are communicating with is an employee. We take your privacy very seriously and confidentially handle your information.