Data Scientist Intern - Equipment Intelligence - Summer/Fall 2026

The group you’ll be a part of

In the Global Products Group, we are dedicated to excellence in the design and engineering of Lam's etch and deposition products. We drive innovation to ensure our cutting-edge solutions are helping to solve the biggest challenges in the semiconductor industry. 

The impact you’ll make

We are seeking a Data Scientist Intern to join the Equipment Intelligence team in the Deposition Product Group. Equipment Intelligence operates at the intersection of physics‑based modeling, big data analytics, machine learning, and advanced control systems. As a Data Scientist Intern, you will collaborate with a team of highly motivated, agile engineers to contribute to:

• Development of analytics pipelines and platforms leveraging big‑data and machine‑learning techniques to support a global installed base of wafer fabrication equipment
• Creation and training of deep learning and machine learning models for equipment performance characterization, anomaly detection, predictive maintenance, and optimization
• Integration of empirical learning methods with physics‑based or first‑principles models
• Exploration, cleaning, and analysis of complex, high‑volume equipment datasets
• Supporting model validation, deployment workflows, and documentation of findings

What you’ll do

In addition to core technical work, the Data Scientist Intern will:

• Collaborate with Hardware, Process, and Software engineering teams to define data requirements and guide data‑driven product development
• Communicate insights, results, and visualizations to internal engineering teams and, when appropriate, global customers
• Participate in experiment planning with engineering teams and support interpretation of experiment results
• Contribute to improving internal tooling, workflows, and automation

Who we’re looking for

Minimum Qualifications

Education

• Currently enrolled in a Bachelor’s or Master’s program in Computer Science, Data Science, Electrical Engineering, Mechanical Engineering, Applied Physics, Materials Science, or a related quantitative field
• Able to intern for at least 3 months preferrably 6-9 months if available. 

Capabilities

• Strong analytical, quantitative, and problem‑solving skills
• Ability to learn new tools, modeling techniques, and domain knowledge quickly
• Ability to work independently on scoped tasks and collaborate effectively within multidisciplinary teams
• Strong written and verbal communication skills

Preferred qualifications

While not required, candidates with the following experience will stand out:

• Coursework or project experience in machine learning, deep learning, statistical learning, or data mining
• Experience building models using modern ML/DL frameworks (e.g., PyTorch, TensorFlow, JAX, Scikit‑learn)
• Familiarity with distributed compute environments (cloud platforms, Spark, Ray, or HPC systems)
• Experience with Python for data science (NumPy, Pandas, Matplotlib, etc.)
• Experience working with large datasets, time‑series data, or sensor/telemetry data
• Familiarity with experiment design, model validation, or data pipelines
• Interest in semiconductor manufacturing, advanced equipment, or applied physics
• Proficiency in Python or similar high‑level languages
• Understanding of core ML/DL concepts and ability to implement models from examples or academic references
• Comfort working with modern development tools (Git, notebooks, VS Code, containerization, etc.)
• Ability to present complex quantitative concepts clearly and visually
• Curiosity and willingness to learn in a highly multidisciplinary environment

Our commitment

We believe it is important for every person to feel valued, included, and empowered to achieve their full potential. By bringing unique individuals and viewpoints together, we achieve extraordinary results.

Lam Research ("Lam" or the "Company") is an equal opportunity employer. Lam is committed to and reaffirms support of equal opportunity in employment and non-discrimination in employment policies, practices and procedures on the basis of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex (including pregnancy, childbirth and related medical conditions), gender, gender identity, gender expression, age, sexual orientation, or military and veteran status or any other category protected by applicable federal, state, or local laws. It is the Company's intention to comply with all applicable laws and regulations. Company policy prohibits unlawful discrimination against applicants or employees.

Lam offers a variety of work location models based on the needs of each role. Our hybrid roles combine the benefits of on-site collaboration with colleagues and the flexibility to work remotely and fall into two categories – On-site Flex and Virtual Flex. ‘On-site Flex’ you’ll work 3+ days per week on-site at a Lam or customer/supplier location, with the opportunity to work remotely for the balance of the week. ‘Virtual Flex’ you’ll work 1-2 days per week on-site at a Lam or customer/supplier location, and remotely the rest of the time.