You’ll work with simulation environments, operational data, and real-world feedback to build intelligent systems that can learn, adapt, and improve complex factory operations.
What You’ll Do
Design, train, evaluate, and deploy machine learning and deep learning models.
Develop reinforcement learning solutions for complex decision-making and optimization problems.
Build RL environments, reward functions, policies, and evaluation frameworks.
Train and optimize agents using simulation and operational data.
Explore techniques including policy optimization, model-based RL, multi-agent systems, and hierarchical learning.
Build scalable training, inference, monitoring, and retraining workflows.
Partner with software engineers to integrate AI capabilities into production and customer-facing products.
Contribute to MLOps, experiment tracking, model versioning, observability, and lifecycle management.
Research and prototype emerging technologies including Generative AI, Agentic AI, LLMs, RAG, and multi-agent systems.
Collaborate with data scientists, software engineers, cloud architects, and semiconductor domain experts.
What We’re Looking For
Required
Strong foundation in machine learning and deep learning.
Hands-on experience building and deploying production ML systems.
Strong Python development skills.
Experience with PyTorch and/or TensorFlow.
Demonstrated experience developing reinforcement learning solutions.
Strong understanding of RL concepts including environments, policies, rewards, value functions, and exploration strategies.
Experience with modern RL methods such as PPO, SAC, DQN, Actor-Critic, or similar approaches.
Experience training and evaluating RL agents in simulation environments.
Ability to formulate complex optimization problems as reinforcement learning problems.
Experience with Git, testing, code reviews, CI/CD, and production software development.
Preferred
Experience building AI agents or autonomous decision-making systems.
Experience with discrete-event simulation or simulation-driven learning.
Experience combining RL with optimization techniques.
Knowledge of scheduling, dispatching, operations research, or industrial optimization.
Experience with Azure, AWS, or Google Cloud, Docker, Kubernetes, or MLflow.
Experience with Generative AI, LLMs, agent frameworks, or RAG.
Semiconductor manufacturing experience is a plus.
Why This Role
Reinforcement learning is a core strategic capability for this team, not simply a research topic. You’ll help develop next-generation manufacturing optimization solutions and intelligent agents capable of learning and adapting to complex factory operations.
You’ll join an experienced, collaborative team of data scientists, AI engineers, software developers, and cloud architects working on challenging industrial AI problems with direct customer and business impact.
Additional Information
Time Type
Full time
Employee Type
Assignee / Regular
Travel
Yes, 10% of the Time
Relocation Eligible
No
The salary offered to a selected candidate will be based on multiple factors including location, hire grade, job-related knowledge, skills, experience, and with consideration of internal equity of our current team members. In addition to a comprehensive benefits package, candidates may be eligible for other forms of compensation such as participation in a bonus and a stock award program, as applicable.
For all sales roles, the posted salary range is the Target Total Cash (TTC) range for the role, which is the sum of base salary and target bonus amount at 100% goal achievement.
Applied Materials is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law.
In addition, Applied endeavors to make our careers site accessible to all users. If you would like to contact us regarding accessibility of our website or need assistance completing the application process, please contact us via e-mail at Accommodations_Program@amat.com, or by calling our HR Direct Help Line at 877-612-7547, option 1, and following the prompts to speak to an HR Advisor. This contact is for accommodation requests only and cannot be used to inquire about the status of applications.
