Applied Materials

1 week ago

AI Engineer - (B5)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 20 hours agoStatus: Live

Job Summary

Build and scale manufacturing data and analytics ecosystems, applying statistical methods, machine learning, and data mining to solve production challenges like yield optimization and predictive maintenance. Design intelligent, agentic workflows that automate data ingestion, feature engineering, model execution, and decision-making. Partner with manufacturing, supply chain, and engineering teams to translate analytics into measurable KPIs and executive-ready insights using production-grade pipelines.

Location: Austin

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Architect and scale manufacturing data ecosystems to ingest, consolidate, and analyze structured and unstructured data from plant, supply chain, and engineering sources.
•Lead advanced analytics and modeling initiatives to apply statistical, machine learning, and data mining techniques to manufacturing problems.
•Build agentic workflows and intelligent automation pipelines that orchestrate ingestion, feature engineering, model execution, and decision-making at scale.
•Define and optimize data architecture, including data acquisition strategies, semantic layers, and scalable data models for real-time analytics and digital twins.
•Translate analytical findings into actionable business outcomes by partnering with manufacturing operations, supply chain, and product engineering teams and communicating executive-ready insights.

Travel: Low travel

Pay and Benefits

Salary: 172,000 - 236,500

Equity and Bonus:Equity

Key Requirements

•10+ years of experience in agent-based systems, AI orchestration frameworks, and workflow automation.
•Deep expertise in advanced analytics, AI/ML, and industrial data systems within manufacturing environments.
•Ability to apply statistical, machine learning, and data mining techniques to solve complex manufacturing problems (e.g., yield optimization, predictive maintenance).
•Experience designing data architecture (data acquisition strategies, semantic layers, scalable data models) for real-time analytics and digital twins.
•Ability to lead and mentor multi-disciplinary teams and communicate complex technical concepts to senior stakeholders.

Experience:10+ yearsManufacturingSupply chainIndustrial dataAgent-based systems

Skills:CommunicationLeadershipMentorshipProblem-solvingStakeholder management

Tech Stack:PythonRSQLAIMachine learningData miningUI/APIDigital twins

Company Brief

Applied Materials

Provides semiconductor manufacturing equipment, services, and software used to build advanced chips and display technologies. Its tools support materials engineering, deposition, etching, inspection, and process control for major electronics manufacturers worldwide.

Industry: Industrial Machinery

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1967

Glassdoor: 3.9

Website LinkedIn Glassdoor

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Applied Materials

1 week ago

AI Engineer - (B5)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 20 hours agoStatus: Live

Job Summary

Location: Austin

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Architect and scale manufacturing data ecosystems to ingest, consolidate, and analyze structured and unstructured data from plant, supply chain, and engineering sources.
•Lead advanced analytics and modeling initiatives to apply statistical, machine learning, and data mining techniques to manufacturing problems.
•Build agentic workflows and intelligent automation pipelines that orchestrate ingestion, feature engineering, model execution, and decision-making at scale.
•Define and optimize data architecture, including data acquisition strategies, semantic layers, and scalable data models for real-time analytics and digital twins.
•Translate analytical findings into actionable business outcomes by partnering with manufacturing operations, supply chain, and product engineering teams and communicating executive-ready insights.

Travel: Low travel

Pay and Benefits

Salary: 172,000 - 236,500

Equity and Bonus:Equity

Key Requirements

•10+ years of experience in agent-based systems, AI orchestration frameworks, and workflow automation.
•Deep expertise in advanced analytics, AI/ML, and industrial data systems within manufacturing environments.
•Ability to apply statistical, machine learning, and data mining techniques to solve complex manufacturing problems (e.g., yield optimization, predictive maintenance).
•Experience designing data architecture (data acquisition strategies, semantic layers, scalable data models) for real-time analytics and digital twins.
•Ability to lead and mentor multi-disciplinary teams and communicate complex technical concepts to senior stakeholders.

Experience:10+ yearsManufacturingSupply chainIndustrial dataAgent-based systems

Skills:CommunicationLeadershipMentorshipProblem-solvingStakeholder management

Tech Stack:PythonRSQLAIMachine learningData miningUI/APIDigital twins

Company Brief

Applied Materials

Industry: Industrial Machinery

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1967

Glassdoor: 3.9

Website LinkedIn Glassdoor