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: $78,500.00 - $108,000.00 Location: Austin,TX You’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 . Responsibilities • Develop and deploy AI, machine learning, and analytics solutions to support Install Automation , Auto Sequencing , Smart Sequencing , and task automation initiatives. • Build predictive and optimization models that improve installation efficiency, resource utilization, workflow execution, and cycle-time performance. • Analyze engineering, installation, service, and operational data to identify patterns, predict outcomes, and drive automation decisions. • Design and implement data pipelines, feature engineering, model training, validation, deployment, and monitoring processes. • Apply machine learning, optimization techniques, and Generative AI to automate engineering workflows, documentation, and decision-making. • Create dashboards and KPI frameworks to measure automation effectiveness, productivity improvements, and business impact. • Partner with Engineering, Manufacturing, Service, and Digital Transformation teams to develop and scale enterprise automation solutions. • Document methodologies, models, and best practices to support adoption across global teams. Requirements • Bachelor's or Master's degree in Data Science, Computer Science, Engineering, Statistics, Artificial Intelligence, or related field. • 3+ years of experience in Data Science, Machine Learning, AI, Advanced Analytics, or Process Automation. • Strong proficiency in Python and machine learning frameworks such as Scikit-Learn, TensorFlow, PyTorch, or equivalent. • Experience developing predictive models, optimization algorithms, recommendation systems, or workflow automation solutions. • Knowledge of supervised and unsupervised learning, deep learning, Generative AI, and statistical modeling. • Experience working with large-scale engineering, manufacturing, service, or operational datasets. • Semiconductor equipment, industrial automation, or field service experience preferred. • Strong analytical, problem-solving, and communication skills with the ability to translate complex data into business value. • Willingness to travel internationally (approximately 10%). Additional Information Time Type: Full time Employee Type: Assignee / Regular Travel: Yes, 10% of the Time Relocation Eligible: Yes 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.

Requirements

Must-haves

Develop and deploy AI, machine learning, and analytics solutions to support Install Automation , Auto Sequencing , Smart Sequencing , and task automation initiatives.
Build predictive and optimization models that improve installation efficiency, resource utilization, workflow execution, and cycle-time performance.
Analyze engineering, installation, service, and operational data to identify patterns, predict outcomes, and drive automation decisions.
Design and implement data pipelines, feature engineering, model training, validation, deployment, and monitoring processes.
Apply machine learning, optimization techniques, and Generative AI to automate engineering workflows, documentation, and decision-making.
Create dashboards and KPI frameworks to measure automation effectiveness, productivity improvements, and business impact.
Partner with Engineering, Manufacturing, Service, and Digital Transformation teams to develop and scale enterprise automation solutions.
Document methodologies, models, and best practices to support adoption across global teams.
Bachelor's or Master's degree in Data Science, Computer Science, Engineering, Statistics, Artificial Intelligence, or related field.
3+ years of experience in Data Science, Machine Learning, AI, Advanced Analytics, or Process Automation.
Strong proficiency in Python and machine learning frameworks such as Scikit-Learn, TensorFlow, PyTorch, or equivalent.
Experience developing predictive models, optimization algorithms, recommendation systems, or workflow automation solutions.
Knowledge of supervised and unsupervised learning, deep learning, Generative AI, and statistical modeling.
Experience working with large-scale engineering, manufacturing, service, or operational datasets.
Strong analytical, problem-solving, and communication skills with the ability to translate complex data into business value.
Willingness to travel internationally (approximately 10%).
Additional Information
Assignee / Regular
Yes, 10% of the Time

Nice-to-haves

Semiconductor equipment, industrial automation, or field service experience preferred.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aigomachine learningpythonaccessibility

Platform: eightfold
Effort: medium