AI Engineer
About the job
- 10+ years of experience in agent-based systems, AI orchestration frameworks, and workflow automation.
- Deep expertise in advanced analytics, artificial intelligence and machine learning, and industrial data systems, with cross-domain knowledge in supply chain, quality, and engineering.
- Ability to anticipate manufacturing, supply chain, and regulatory challenges and recommend data-driven process, product quality, and operational efficiency improvements.
- Ability to align analytics initiatives with strategic business priorities and drive measurable impact across cost, throughput, yield, and cycle time.
- Ability to solve highly complex, ambiguous, high-impact problems using analytical approaches including artificial intelligence-driven simulations, optimization models, and graph-based reasoning.
- Ability to design end-to-end intelligent systems integrating data, models, and decision logic into automated workflows.
- Ability to communicate complex technical concepts to senior stakeholders and drive alignment across cross-functional teams.
- Architect and scale manufacturing data ecosystems by designing and implementing methods, processes, and systems to ingest, consolidate, and analyze structured and unstructured data from plant, supply chain, and engineering sources.
- Lead advanced analytics and modeling initiatives using statistical, machine learning, and data mining techniques, including Python and R, to solve manufacturing problems such as yield optimization, predictive maintenance, and constraint resolution.
- Build autonomous, artificial intelligence-powered pipelines that orchestrate data ingestion, feature engineering, model execution, and decision-making at scale, reducing manual intervention and accelerating time-to-insight.
- Define and optimize data architecture, including data acquisition strategies, semantic layers, and scalable data models supporting real-time analytics, digital twins, and artificial intelligence-driven manufacturing use cases.
- Partner with manufacturing operations, supply chain, and product engineering teams to define key performance indicators, uncover insights, and operationalize recommendations.
- Develop production-grade analytics solutions by designing algorithms, models, and automation pipelines leveraging SQL, Python, and modern data platforms to cleanse, integrate, and process large-scale industrial datasets.
- Collaborate with product, engineering, and operations teams to frame hypotheses, design experiments, and uncover correlations beyond current measurement systems.
- Translate complex analytical findings into clear narratives and visualizations to influence senior leadership decision-making and operational strategies.
- Influence strategic direction, investment decisions, and resource allocation for analytics and artificial intelligence programs within manufacturing.
- Establish best practices for data products, automation frameworks, and artificial intelligence adoption across global operations.
- Lead and mentor multidisciplinary data science, engineering, analytics, and UI/API teams to deliver production-ready solutions.
About the company
Applied Materials designs and builds precision machines that chipmakers and display manufacturers use to form, shape and inspect thin layers of material. Its platforms handle steps such as depositing films and removing unwanted material, helping chipmakers create transistors and wiring at atomic scale. Customers include makers of logic chips and memory, as well as manufacturers of advanced displays. The company earns money from equipment sales, replacement parts and services, and factory software that schedules production and monitors manufacturing processes. Applied Materials was founded in 1967 and is headquartered in Santa Clara, California.
Company Size
10,001+
Company Stage
IPO
Headquarters
Santa Clara, California
Founded
1967
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Simplify's Take
What believers are saying
- Installed equipment brings repeat business: Applied Global Services sells long-term service agreements, replacement parts and equipment upgrades.
- Sales are expanding: Applied's August 2026 report showed fiscal Q3 revenue of $9.12 billion, up 25% yearly.
- Employees join profitable operations: Applied reported $3.08 billion of operating profit for fiscal Q3 in August 2026.
What critics are saying
- Singapore manufacturing hires face late shifts: Applied's live engineering posting specifies 4 p.m. to 1:30 a.m. schedules.
- Export compliance has real costs: Applied and its Korea subsidiary settled a $252 million penalty in February 2026.
- Sales depend on China access: Applied's December 2025 filing attributed 30% of fiscal 2025 revenue to customers there.
What makes Applied Materials unique
- Applied combines manufacturing steps under vacuum: its Endura copper platform integrates seven processes to protect delicate material interfaces.
- Factory software reaches beyond chips: Applied SmartFactory serves battery and pharmaceutical manufacturers alongside semiconductor plants.
- Research targets future chip generations: Applied's EPIC partners work on technology three to four generations ahead of production.
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Benefits
Health Insurance
Dental Insurance
Vision Insurance
Life Insurance
Disability Insurance
Relocation Assistance
Performance Bonus
Stock Options
Flexible Work Hours
Growth & Insights and Company News
6 month growth
0%1 year growth
-1%2 year growth
-1%A Motley Fool comparison of chip equipment maker Applied Materials and chipmaker Intel favours Applied Materials as the better 2026 buy, though the author suggests buying shares gradually. Applied Materials' revenue rose 25% to $9.1 billion in the quarter ended July 26, 2026, and net income rose 43% to $2.5 billion. Risks include cyclical demand and China, which made up 28% of revenue. In February 2026 it agreed to pay $252.5 million to settle US export allegations. Intel's second-quarter revenue also rose 25%, to $16.1 billion. It posted an $11.0 billion net loss, driven by a $12.5 billion noncash charge tied to its US government deal. Its foundry unit lost $2.1 billion, and an August share sale raising about $23 billion diluted existing owners. On valuation, Applied trades at 42.2x forward earnings against Intel's 77.7x.
Applied Materials (NASDAQ:AMAT) expects to gain more than two percentage points of wafer-fab-equipment market share by 2030, driven by demand for artificial intelligence (AI) chips. The company outlined its strategy at the SEMICON West technology breakfast. Chief executive officer Gary Dickerson said AI spending is concentrating in leading-edge logic, DRAM memory and advanced packaging, which should make up about 75% of incremental industry growth. For 2030, Applied targets a 54% non-GAAP gross margin, a 40% operating margin and more than $12 billion in services revenue. It expects more than $1 billion in high-bandwidth-memory packaging revenue this year. The company plans to more than double its laboratory and manufacturing capacity, and return 80% to 100% of free cash flow to shareholders.
Applied Materials stock trades at 39.5 times adjusted earnings for the past twelve months, despite sales growth of just 7.8% over the period. The price leans on forecasts that sales will rise 36.3% between fiscal 2026 and fiscal 2027, with profit growing 40.0%. Net margin is expected to widen from 27% in fiscal 2025 to 31% in fiscal 2027. On those estimates, the stock costs 38.7 times fiscal 2026 profit and 27.7 times fiscal 2027 profit. Sales growth reached 24.8% in the most recent quarter, up from declines earlier in the year. Management said clean room space at customers' factories will limit shipments in 2027, and costs could squeeze margins. The company presents to investors on October 13, 2026, at SEMICON West.
Applied Materials chief executive officer Gary Dickerson called AI the biggest economic "inflection" point of our lifetime. He spoke about the company's $5 billion EPIC Center in Silicon Valley, its research into next-generation chips, and surging demand for AI chips. Dickerson made the remarks on "The Claman Countdown.
Applied Materials unveiled its Equipment and Process Innovation and Commercialization (EPIC) Center in Sunnyvale, California, on October 12, 2026. The $5 billion facility is billed as the world's largest dedicated to collaborative semiconductor process technology and equipment R&D. Chipmakers, systems companies, equipment partners and universities will work alongside Applied's engineers. Founding partners are TSMC, Intel, Samsung Electronics, Micron and SK hynix. Broadcom, Advantest, SCREEN, KIOXIA and Besi join as innovation partners, along with five research universities. The 600,000-square-foot building holds nearly four acres of cleanroom space. It aims to remove the handoffs between materials research, equipment development and pilot production, speeding new chip technologies to volume manufacturing for the AI era. Applied expects capital spending to scale to about $5 billion as customer projects begin.