Pay
In line with similar jobs
$184K–$253K against $166K–$240K, the middle half of what similar US postings state.
From 1,319 postings in the last year. Stated ranges, not salaries paid.
AI/ML Engineer
Santa Clara, CA, United States
Actively hiring, first seen by us 9 days ago- Pay
$184,000–253,000/yearAnnual period assumed — pay source
Salary: $184,000.00 - $253,000.00 Location:
Read the full posting- Work setting
- Not stated
- Employment
Full-time — employment source
Time Type: Full time Employee Type:
Read the full posting
What you’ll work on
Full postingJoin Applied Materials AI COE team to build intelligent systems that solve complex problems in semiconductor manufacturing.
As an AI / Machine Learning Engineer, you’ll design, develop, and deploy production AI solutions across machine learning, deep learning, reinforcement learning, and AI agents.
Build RL environments, reward functions, policies and evaluation frameworks
Design, train and deploy machine learning and deep learning models
Develop RL solutions for factory scheduling and optimization decisions
Build scalable training, inference, monitoring and retraining workflows
Partner with software engineers to integrate AI into production products
From the employer’s posting
Join Applied Materials AI COE team to build intelligent systems that solve complex problems in semiconductor manufacturing.
As an AI / Machine Learning Engineer, you’ll design, develop, and deploy production AI solutions across machine learning, deep learning, reinforcement learning, and AI agents. A key focus of this role is using reinforcement learning (RL) to optimize dynamic manufacturing decisions such as scheduling, dispatching, planning, and resource allocation.
Build RL environments, reward functions, policies, and evaluation frameworks.
Design, train, evaluate, and deploy machine learning and deep learning models.
Develop reinforcement learning solutions for complex decision-making and optimization problems.
Build scalable training, inference, monitoring, and retraining workflows.
Partner with software engineers to integrate AI capabilities into production and customer-facing products.
What you’ll bring
All qualificationsCore experience
- 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 reinforcement learning experience (PPO, SAC, DQN, Actor-Critic or similar)
Qualification wording
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.
Experience with modern RL methods such as PPO, SAC, DQN, Actor-Critic, or similar approaches.
About Applied Materials
Applied Materials is the global leader in materials science and engineering solutions that are at the foundation of virtually every new semiconductor chip and advanced display in the world.
In the employer’s words · Read in context
Posting record
Report an errorActively hiringFirst seen by us 9 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 29, 20269 days ago
- Recorded sightings
- 10
- Last seen by us
- Nov 7, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 9
Similar jobs usually come down between day 7 and day 71.
At Applied Materials, jobs usually come down by about day 41.
From 4,662 similar postings that came down, and 49 of Applied Materials’s. Coming down is not always a hire.
Applied Materials is hiring
23 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring at a steady pace
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- AWS
- Azure
- Docker
- Kubernetes
- MLflow
- PyTorch
- TensorFlow
- GCP
Where the posting names them
- Hands-on experience building and deploying production ML systems. - Strong Python development skills. - Experience with PyTorch and/or TensorFlow.
- 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.
- Strong Python development skills. - Experience with PyTorch and/or TensorFlow. - Demonstrated experience developing reinforcement learning solutions.
Your next step
Complete your application on jobs.appliedmaterials.com. The employer’s form will show what is required.
Applying through Radancy (TalentBrew)
- Radancy (TalentBrew) runs the employer’s careers site, but the application itself usually runs on another system, often Workday or Taleo. The advice for that system applies once you click Apply.
Already applied? Track this application
About Applied Materials
- People
- About 36,500 in 2025, up 2% from the year before.Annual report (SEC Form 10-K)
- Company
- Listed as AMAT.
- H-1B visas
- 209 approved for new hires in fiscal 2025.US Citizenship and Immigration Services
Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
Who We Are
Applied Materials is the global leader in materials science and engineering solutions that are at the foundation of virtually every new semiconductor chip and advanced display in the world. The equipment that we create and service is essential to advancing AI and accelerating the commercialization of next-generation semiconductor chips. Join us and push the boundaries of materials science and engineering in a company at the foundation of the electronics industry. The work we do together advances the world’s technology.
What We Offer
Salary:
$184,000.00 - $253,000.00Location:
Santa Clara,CAYou’ll benefit from a supportive work culture that encourages you to learn, develop, and grow your career as you take on challenges and drive innovative solutions for our customers. We empower our team to push the boundaries of what is possible—while learning every day in a supportive leading global company. Visit our Careers website to learn more.
At Applied Materials, we care about the health and wellbeing of our employees. We’re committed to providing programs and support that encourage personal and professional growth and care for you at work, at home, or wherever you may go. Learn more about our benefits.
Role Overview
Join Applied Materials AI COE team to build intelligent systems that solve complex problems in semiconductor manufacturing.
As an AI / Machine Learning Engineer, you’ll design, develop, and deploy production AI solutions across machine learning, deep learning, reinforcement learning, and AI agents. A key focus of this role is using reinforcement learning (RL) to optimize dynamic manufacturing decisions such as scheduling, dispatching, planning, and resource allocation.
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 timeEmployee Type:
Assignee / RegularTravel:
Yes, 10% of the TimeRelocation Eligible:
NoThe 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.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Salary: $184,000.00 - $253,000.00 Location:
- Location & working pattern
Santa Clara, CA, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
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.