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ServiceNow

Machine Learning Engineer Intern - Summer 2026

Posted Yesterday
Remote or Hybrid
Hiring Remotely in Santa Clara, CA
55-63
Internship
Remote or Hybrid
Hiring Remotely in Santa Clara, CA
55-63
Internship
The intern will enhance natural language processing capabilities using deep learning algorithms, engage in data collection, and develop AI/ML solutions.
The summary above was generated by AI
Company Description
It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today - ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone.
Job Description
Role Overview
As a Machine Learning Engineering Intern, you will work alongside skilled engineers to enhance ServiceNow's natural language processing capabilities using advanced deep learning algorithms. You'll engage in data collection, synthetic data generation, and utilize customer data to bolster workflow intelligence. This internship offers hands-on experience in developing AI/ML solutions, cultivating innovative ideas, and contributing to projects that elevate user experiences and workflow efficiency. You will thrive in a dynamic and collaborative environment, laying a foundation for career growth.
Qualifications
Required Qualifications
  • Current enrollment in a full-time Bachelor's or Master's program in AI, Machine Learning, Data Science, Computer Science or a related discipline at an accredited university.
  • Graduating December 2026, or later
  • Must be able to obtain and maintain authorization to work.
  • Commit to a 12-week internship in Summer 2026 (May-August, or, June-September)
  • Capable of operating on a hybrid schedule from one of our office locations.
  • Strong theoretical and practical knowledge of Machine Learning/Deep Learning.
  • Understanding of machine learning fundamentals, including supervised/unsupervised learning, model evaluation, and optimization.
  • Practical experience in systematically designing, building, evaluating, and productionizing machine learning solutions.
  • Proficient in prompt engineering and developing LLM based features
  • Proficiency in multiple programming languages: Java, Python, JavaScript, and SQL; familiarity with ML libraries such as NumPy, Pandas, Scikit-learn, TensorFlow/PyTorch.
  • Innovative problem-solving skills for complex software challenges.
  • Strong communication skills and experience in diverse cross-functional teams.

Preferred Qualifications
  • Experience in using Al productivity tools such as Cursor, Windsurf, etc.
  • Experience with cloud platforms like AWS, GCP, or Azure and associated ML services.
  • Familiarity with MLOps tools like MLflow, Kubeflow, and Weights & Biases.
  • Knowledgeable about containerization and orchestration technologies.
  • Understanding of relational databases such as MySQL or Oracle.
  • Up-to-date with recent advances in AI research, including NLP/NLU and deep learning architectures.
  • Prior experience from internships, academic projects, coding competitions, or publications.

For positions in this location, we offer a base pay of $55.18 - $63.35/hour, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location.
Additional Information
Work Personas
We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.
Equal Opportunity Employer
ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.
Accommodations
We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact [email protected] for assistance.
Export Control Regulations
For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities.
From Fortune. ©2025 Fortune Media IP Limited. All rights reserved. Used under license.

Top Skills

AWS
Azure
GCP
Java
JavaScript
Kubeflow
Mlflow
MySQL
Numpy
Oracle
Pandas
Python
PyTorch
Scikit-Learn
SQL
TensorFlow
Weights & Biases

ServiceNow Los Angeles, California, USA Office

Los Angeles, CA, United States, 92660

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