NM Si Manufacturing Area Industrial Engineer

Job Details:

Job Description: 

The NMSi Industrial Engineering team provides both tactical and strategic operational support to the factory, ensuring capacity is available to support technology development and manufacturing ramps. The team is responsible for establishing and maintaining systems and processes that enable affordability targets, as well as defining equipment and layout plans that support and sustain factory output and performance commitments across multiple concurrent technology nodes.

Key responsibilities include developing and implementing capacity analysis methodologies, capital forecasting, capacity planning, and equipment constraint assessments to support technology development, startup, and ramp activities. The role also involves maintaining module-level capacity models to reflect process changes, identifying continuous improvement opportunities, and driving operational efficiencies.

This position requires the ability to translate complex data, systems outputs, and analytical findings into clear recommendations and actionable insights for stakeholders across the organization. The successful candidate will partner closely with Global Supply Management, Finance, Process Engineering, Production, Automation, Central IE teams, Fab Management, Installation and Equipment Qualification teams, and Industrial Engineering peers across Intel sites to support strategic objectives and successful technology ramps.

Key Responsibilities

• Analyze capacity requirements to support wafer start plans across multiple technologies.
• Develop, maintain, and validate capacity models for existing and first-of-a-kind equipment.
• Perform output and return-on-investment (ROI) analyses for proposed changes impacting factory capacity.
• Evaluate cycle time, cost, and equipment performance against established goals.
• Support the implementation and optimization of operational systems that improve output, productivity, and efficiency.
• Analyze key manufacturing metrics and drive improvements through Lean methodologies and data-driven decision-making.
• Identify and implement continuous improvement opportunities to enhance factory performance and operational effectiveness.

Preferred Behavioral Traits

• Strong verbal and written communication skills, active listening skills, and the ability to thrive in ambiguous environments.
• Proven ability to collaborate effectively across organizational boundaries and drive solutions through partnership and influence.
• Demonstrated success working within high-performing teams, setting high expectations, driving accountability, and delivering results with urgency.
• Strong initiative, learning agility, and ability to work independently.
• Excellent analytical, computer, and systems skills.
• Experience applying Model-Based Problem Solving methodologies.
• Proven track record of leading improvement initiatives and strategic roadmaps across multiple organizations.
• Strong leadership and influencing skills, with the ability to drive change and improve organizational performance.

Qualifications:

Minimum Qualifications:

• Minimum of a Bachelor of Science degree or Master of Science degree in Chemical Engineering, Materials Science & Engineering, Electrical Engineering, Physics, or Mechanical Engineering or any related field.
• Bachelor's degree with 3+ years of relevant experience, or Master's degree with 2+ years of relevant experience, in manufacturing science, data analysis, and project/program management.
• 1+ of experience with one or more data analytical tools such as MS Excel, JMP, MiniTab, or SQL Pathfinder with basic understanding of data structures/query fundamentals and experience with scripting languages.
• 1+ years of experience/knowledge in operations research including theory of constraints, supply chain management and factory physics.

Preferred Qualifications:

• Data extraction and analysis experience with tools such as R, Python, SQL, C, or C++ desired.
• Optimization and Simulation expertise.
• Financial/cost/ROI analysis.
• Strong statistics knowledge and application.
• Knowledge of Lean and Six Sigma methodologies and applications.

Job Type:

Experienced Hire

Shift:

Shift 1 (United States of America)

Primary Location: 

US, New Mexico, Albuquerque

Additional Locations:

Posting Statement:

All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.

Position of Trust

N/A

Benefits

We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock bonuses, and benefit programs which include health, retirement, and vacation. Find out more about the benefits of working at Intel.

Annual Salary Range for jobs which could be performed in the US: $89,010.00-125,660.00 USDThe range displayed on this job posting reflects the minimum and maximum target compensation for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific compensation range for your preferred location during the hiring process.

Work Model for this Role

This role will require an on-site presence. * Job posting details (such as work model, location or time type) are subject to change.

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ADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.