Data Science Intern – LLM & Agentic AI Evaluation

Who are we?

A career at Equinix means being at the center of shaping what comes next and amplifying customer value through innovation and impact. You’ll work across teams, influence key decisions, and help shape the path forward. You’ll find belonging, purpose, and a team that welcomes you—because when you feel valued, you’re empowered to do your best work.

Job Summary

We are seeking a research-oriented Data Science Intern to support the testing, evaluation, and validation of LLM-driven systems within the Equinix Sidekick and Agentic AI Platform. This role is ideal for a PhD scholar with a strong foundation in machine learning, deep learning, and generative AI, who is interested in applying research rigor to real-world, enterprise-scale AI systems.

The intern will focus on analysing model behaviour, identifying failure modes, benchmarking performance, and improving reliability of agent-based workflows, working closely with AI engineers and platform teams.

This role is well suited for PhD candidates from IISc, IITs, or IIITs, with demonstrated experience in ML research, model evaluation, and Python-based experimentation.

Responsibilities

• Design and conduct systematic evaluations of LLM-powered assistants and agent workflows used in Sidekick

• Build Python-based experimentation and testing pipelines for analysing model outputs, reasoning quality, and robustness

• Evaluate LLM and agent behaviour across metrics such as accuracy, consistency, error patterns, hallucination risk, and qualitative output quality

• Apply concepts from transformers, attention mechanisms, and generative models to understand and improve system behaviour

• Perform error analysis and ablation studies to identify weaknesses in prompts, tools, or reasoning flows

• Support benchmarking of different model architectures or configurations in controlled experimental settings

• Document findings in a structured manner suitable for engineering teams and leadership stakeholders

Qualifications

Required

• Currently pursuing a PhD/Masters by Research in Computer Science, AI/ML, Data Science, or related disciplines from IISc, IITs, or IIITs

• Strong proficiency in Python for data analysis, modelling, and experimentation

• Solid foundation in Machine Learning and Deep Learning, including supervised learning, neural networks, and transformers

• Hands-on experience with Generative AI / LLMs, including transformer-based architectures

• Experience evaluating ML models using quantitative metrics and qualitative analysis

• Strong research mindset with ability to design clean experiments and communicate insights clearly

Good to Have (Aligned to Profile Growth)

• Experience with image–text or multimodal models, CNNs, Transformers, or attention-based architectures

• Familiarity with LLM frameworks or APIs (e.g. OpenAI, Gemini, Hugging Face, LangChain-style abstractions)

• Exposure to agentic concepts such as tool usage, reasoning chains, or multi-step decision workflows

• Prior publications or research experience demonstrating strong analytical depth

• Interest in applied AI systems deployed at enterprise scale

What You’ll Gain

• Opportunity to apply research-grade ML and GenAI skills to production-adjacent enterprise AI platforms

• Exposure to agentic AI system design, evaluation, and operational considerations

• Mentorship from senior AI platform engineers and applied researchers at Equinix

• Hands-on experience bridging academic research and real-world AI systems

Equinix is committed to ensuring that our employment process is open to all individuals, including those with a disability.  If you are a qualified candidate and need assistance or an accommodation, please let us know by completing this form.

Equinix is an Equal Employment Opportunity and, in the U.S., an Affirmative Action employer.  All qualified applicants will receive consideration for employment without regard to unlawful consideration of race, color, religion, creed, national or ethnic origin, ancestry, place of birth, citizenship, sex, pregnancy / childbirth or related medical conditions, sexual orientation, gender identity or expression, marital or domestic partnership status, age, veteran or military status, physical or mental disability, medical condition, genetic information, political / organizational affiliation, status as a victim or family member of a victim of crime or abuse, or any other status protected by applicable law. 

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This posting is a new position within our organization.