Applied Materials

1 week ago

Manager, Data Scientist

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 13 hours agoStatus: Live

Job Summary

Lead the architecture, design, and implementation of agentic AI and multi-agent systems to tackle complex business and manufacturing challenges. Drive hands-on development of AI agents using modern orchestration frameworks, building scalable enterprise AI platforms with RAG, knowledge graphs, and memory management. Establish LLMOps, governance, evaluation, and observability best practices, collaborate cross-functionally, mentor AI engineers and data scientists, and deliver production deployments with measurable business value.

Location: Austin

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Manager level

Key Responsibilities

•Lead the architecture, design, and implementation of agentic AI solutions and multi-agent systems for business and manufacturing challenges.
•Develop AI agents using frameworks such as LangGraph, AutoGen, CrewAI, Semantic Kernel, OpenAI Agents, and Azure AI Foundry.
•Build scalable enterprise AI platforms including agent orchestration, memory management, tool integration, RAG, knowledge graphs, ontologies, and enterprise AI architectures.
•Establish AI engineering best practices for LLMOps, AI governance, evaluation, observability, security, safety, prompt/context engineering, and continuous improvement.
•Collaborate with business stakeholders and technical teams, lead PoCs and production deployments, and mentor AI engineers and data scientists.

Travel: Medium travel

Pay and Benefits

Salary: USD 176,000 - 242,000 annually

Equity and Bonus:Equity

Key Requirements

•Bachelor’s degree in Computer Science, Artificial Intelligence, or Data Science.
•Recognized expertise in generative AI, agentic AI, multi-agent architectures, and enterprise AI platforms.
•Deep knowledge of LLMs, RAG, vector databases, knowledge graphs, AI orchestration frameworks, machine learning, and cloud-native architectures.
•Strong hands-on software engineering experience with Python and modern AI development frameworks.
•Proven ability to design scalable, production-ready AI systems across multiple technology domains.

Experience:Generative AIAgentic AIMachine LearningManufacturingSaaS

Education:Bachelor's in Computer Science, Artificial Intelligence or Data Science

Skills:LeadershipCross-functional collaborationCommunicationMentorshipProblem-solving

Tech Stack:LangGraphAutoGenCrewAISemantic KernelOpenAI AgentsAzure AI FoundryAzure AIDatabricksPythonVector databasesGraph databasesRetrieval-Augmented Generation (RAG)Knowledge graphsOntologiesLLMOpsObservabilityModel optimization

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

Manager, Data Scientist

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 13 hours agoStatus: Live

Job Summary

Location: Austin

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Manager level

Key Responsibilities

•Lead the architecture, design, and implementation of agentic AI solutions and multi-agent systems for business and manufacturing challenges.
•Develop AI agents using frameworks such as LangGraph, AutoGen, CrewAI, Semantic Kernel, OpenAI Agents, and Azure AI Foundry.
•Build scalable enterprise AI platforms including agent orchestration, memory management, tool integration, RAG, knowledge graphs, ontologies, and enterprise AI architectures.
•Establish AI engineering best practices for LLMOps, AI governance, evaluation, observability, security, safety, prompt/context engineering, and continuous improvement.
•Collaborate with business stakeholders and technical teams, lead PoCs and production deployments, and mentor AI engineers and data scientists.

Travel: Medium travel

Pay and Benefits

Salary: USD 176,000 - 242,000 annually

Equity and Bonus:Equity

Key Requirements

•Bachelor’s degree in Computer Science, Artificial Intelligence, or Data Science.
•Recognized expertise in generative AI, agentic AI, multi-agent architectures, and enterprise AI platforms.
•Deep knowledge of LLMs, RAG, vector databases, knowledge graphs, AI orchestration frameworks, machine learning, and cloud-native architectures.
•Strong hands-on software engineering experience with Python and modern AI development frameworks.
•Proven ability to design scalable, production-ready AI systems across multiple technology domains.

Experience:Generative AIAgentic AIMachine LearningManufacturingSaaS

Education:Bachelor's in Computer Science, Artificial Intelligence or Data Science

Skills:LeadershipCross-functional collaborationCommunicationMentorshipProblem-solving

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