Intel Corporation is hiring for a FRESHER entry level Machine Learning Engineer role in India

Position:

• Machine Learning Engineer
• Entry level role designed for fresh graduates and early career researchers
• Focused on combining machine learning, physics based simulations, and advanced semiconductor modeling
• Aligned with Intel Foundry and next generation transistor development initiatives

Company:

• Intel Corporation
• Global semiconductor and computing technology organization
• Known for large scale innovation in processors, platforms, and manufacturing technologies
• Employer with strong emphasis on research, engineering excellence, and long term impact

Location:

• Bengaluru, Karnataka, India
• Part of Intel’s India engineering and research ecosystem
• Works closely with global teams including the United States and other international locations

Job type:

• Full time
• College graduate focused role
• Long term career oriented position with scope for growth within Intel

Job mode:

• Hybrid
• Combination of on site work at Intel Bengaluru campus and off site work
• Designed to support collaboration while offering flexibility

Job requisition id:

• Not explicitly specified in the public posting
• Internal tracking managed by Intel hiring systems

Years of experience:

• Entry level
• Research and project experience gained through PhD work, academic projects, internships, or thesis research is considered valid

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Company description:

• Intel Corporation is a global technology leader with a mission centered on shaping the future of computing and improving life through technology
• The company plays a foundational role in powering devices, systems, and platforms used by individuals, enterprises, and governments worldwide
• Intel operates across semiconductor design, manufacturing, packaging, and system level solutions, making it one of the most influential names in the technology ecosystem
• Intel Foundry is a major business group focused on delivering advanced semiconductor manufacturing capabilities to customers across logic, memory, analog, and emerging device domains
• The organization invests heavily in research, manufacturing innovation, and process technology to support the demands of the AI era and data driven computing
• Employees work in a collaborative environment that brings together experts from physics, materials science, electrical engineering, computer science, and applied mathematics
• Intel emphasizes responsible innovation, inclusion, ethical hiring practices, and equal opportunity across all geographies
• The company provides a structured environment where learning, mentorship, and cross functional exposure are part of everyday work
• With operations spanning multiple continents, Intel offers exposure to global teams, diverse problem statements, and complex engineering challenges
• Intel’s long term vision focuses on creating technologies that remain relevant for decades while contributing to a more connected and intelligent world

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Profile overview:

• The TCAD Machine Learning Engineer role is designed for individuals who enjoy working at the intersection of engineering, physics, and software development
• This role focuses on building, training, and improving machine learning models that support physics based simulation tools used in semiconductor development
• Engineers in this position work on software solutions that enable accurate modeling of next generation transistors at extremely advanced technology nodes
• The role involves translating theoretical models and experimental data into reliable, scalable, and production ready software systems
• Candidates are expected to contribute across the full lifecycle of machine learning tools, from initial concept and prototyping to deployment and long term maintenance
• The position requires close collaboration with application engineers, experimental researchers, and process development teams across multiple regions
• Engineers help convert proof of concept models into robust solutions that can be used by a wider engineering community
• The work directly impacts logic, memory, and analog device scaling strategies for industry leading semiconductor products
• This role is suitable for individuals who enjoy debugging complex systems, optimizing computational performance, and working with scientific data
• It offers exposure to advanced device physics, numerical modeling, and large scale simulation workflows within a real world manufacturing context

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Qualifications:

• Currently pursuing or recently completed a PhD in Electrical Engineering, Physics, Mechanical Engineering, Chemical Engineering, Mathematics, Computer Science and Engineering, or related disciplines with a strong software orientation
• Research or thesis experience involving machine learning or deep learning model development
• Academic or project based experience in software development, including writing, testing, and maintaining code
• Proficiency in Python, C, C++, or similar programming languages used for scientific and engineering applications
• Familiarity with building and maintaining software systems, including basic understanding of backend and frontend concepts
• Understanding of data structures, algorithms, and core programming principles
• Knowledge of statistics, linear algebra, and numerical methods applied in engineering or scientific contexts
• Exposure to solid state device physics or semiconductor fundamentals through coursework or research
• Experience gained through coursework, labs, internships, or collaborative research projects is considered relevant
• Ability to communicate technical ideas clearly to cross functional teams with different domain expertise

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Additional info:

• Responsibilities include developing and training new machine learning models tailored for physics based simulations
• Improving existing machine learning tools by enhancing accuracy, performance, and usability
• Adding new features to established software systems while ensuring stability and reliability
• Debugging complex issues within simulation and machine learning pipelines
• Writing and maintaining test cases to ensure long term software quality
• Supporting application engineers by addressing feature requests and resolving technical challenges
• Working closely with global teams to align development priorities and deliver consistent solutions
• Maintaining and improving software infrastructure used for simulation workflows
• Developing physical models that capture real device and process behavior
• Analyzing fundamental challenges encountered during advanced technology development
• Collaborating with experimental, process, and design teams to define experiments and interpret results
• Presenting recommendations that support scaling strategies for advanced semiconductor devices
• Access to benefits that support physical health, mental well being, and work life balance
• Participation in an inclusive workplace that values diversity, collaboration, and professional growth
• Opportunity to contribute to technologies that influence global computing platforms and products

Please click here to apply.