Intern Applied AI Early Career Engineer

As an Applied AI Early Career Engineer in the AI Lab, you will collaborate with a team to produce top quality research. You will collaborate with our team to develop innovative AI proof-of-concepts (PoCs).

Your role includes working closely with Product Managers and Engineers to clarify project objectives, define success criteria, and assess risks. You will tackle complex problems, design and evaluate machine learning models, and analyze datasets. Reporting on performance, conducting error analysis, and iterating on results are key to delivering impactful AI capabilities.

Key duties also include clear documentation of methods and results and presenting your findings and recommendations to both technical and non-technical stakeholders.

This full-time, 6-month paid program offers a unique opportunity to stay at the forefront of AI research while contributing to meaningful product development.

What you’ll gain

• Mentorship from experienced researchers and engineers.
• Exposure to real product problems and decision-making.
• Opportunity to publish internal findings, explore patent opportunities and potentially co-author papers where appropriate.
• A robust portfolio of PoCs and measurable impact on ServiceNow products.

How to apply

• Resume/CV and unofficial transcript
• Brief cover letter (1–2 paragraphs) describing your research interests and a PoC or research project you’re proud of
• Links to publications, preprints, GitHub, or portfolio (if available)

Qualifications:

• Currently enrolled in a Master’s or PhD program in Computer Science, AI, or a closely related field; or a recent graduate (within the last 12 months) from such a program.
• Graduated no earlier than December 2024.
• Bachelor’s and Masters degree in Computer Science or related fields.
• Must be able to obtain and maintain authorization to work.
• Capable of committing to a full-time schedule starting November 3, 2025-March 31, 2026.
• Demonstrated skills in machine learning (coursework, research, internships, open-source contributions, or substantial projects).
• Demonstrated skills in probability, statistics, and data science
• Ability to rapidly create AI agents and apps using LLM APIs and coding enhancement tools such as Cursor/Windsurf, Codex or Claude
• Ability to implement, train, and evaluate machine learning models (e.g., classical ML, deep learning, NLP/LLMs, retrieval, or multimodal as relevant).
• Proficiency in Python and at least one ML framework (e.g., PyTorch or TensorFlow); solid understanding of data handling, experimentation, and evaluation.
• Strong analytical, problem-solving, and communication skills.
• Ability to work both independently and collaboratively in a fast-paced research environment.

Preferred qualifications

• Prior research experience in AI/ML; publications in peer-reviewed venues (conferences, journals, or workshops).
• Experience with LLMs and modern NLP (prompting, fine-tuning, RAG), vector databases, and evaluation methodologies.
• Experience with MLOps or cloud (AWS, Azure, or GCP), experiment tracking, and reproducibility best practices.

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