Data Science Student for AI Solutions Group

Job Details:

Job Description:

Who We Are?

Intel's AI Solutions Group is at the forefront of innovation, delivering state-of-the-art AI capabilities that power Intel's global chip development.
Our team of over 250 AI Engineers—primarily based in Israel—is driving one of the most impactful transformations inside Intel.
Over the past few years, we've launched over 1,000 AI solutions, used millions of times each day. In recognition of our impact, the team was honored with Intel's Top Performing Organization Award globally in 2024. We're innovating with advanced techniques in AI and Generative AI, redefining how silicon development is done.
We are deeply committed to the growth and development of our people. If you're a brilliant, curious, and kind-hearted individual looking to work on meaningful AI challenges—this is the place to thrive.

We have the dream job for AI Engineers: we build agentic systems that reason, plan, and act — combining LLMs, retrieval, and tool use to solve challenging, high-value problems across text, structured data, and multi-step workflows. We work hands-on with AI agents, RAG pipelines, and LLM orchestration, and we build on frameworks like LangGraph, LangChain, and the broader Python AI ecosystem.

Our AI Engineers are at the core of any new solution we develop, and they're involved in all aspects of the project: from ideation and problem formulation, through designing and prototyping agentic architectures, to preparing solutions for production deployment.

Our large community of AI Engineers and Data Scientists enables you to work and learn with great minds, participate in internal seminars and courses, and take part in leading professional conferences, ensuring you'll constantly grow your skills and knowledge.

Qualifications:

What are we looking for?

• MSc/PhD student focusing on AI, computer science, engineering, or a related field (thesis in a relevant area is a plus).
• Hands-on experience building with LLMs — e.g. prompting, fine-tuning, evaluation, or working with LLM APIs.
• Practical experience with agentic frameworks and concepts: agent orchestration, tool use, multi-step planning, or frameworks such as LangGraph or LangChain.
• Experience with or strong understanding of RAG (Retrieval-Augmented Generation) — embeddings, vector stores, retrieval pipelines.
• Solid foundational ML/DL knowledge (this is a supporting skill, not the core focus of the role).
• Substantial experience programming in Python, including building and integrating multi-component systems (not just notebooks/scripts).
• Highly motivated to solve real-world problems and create high impact in practice.
• Team player with great communication skills, who can also work independently and methodically.
• Capacity to work at least 2.5 days a week, with studies expected to continue for at least 1.5 years.

Job Type:

Student / Intern

Shift:

Shift 1 (Israel)

Primary Location:

Israel, Petah-Tikva

Additional Locations:

Israel, Haifa

Business group:

The Central Engineering Group (CEG) is Intel's data-driven organization that builds scalable engineering solutions across three pillars: Product Enablement (IP, tools, and methodologies), Custom ASIC (leveraging existing IP for custom silicon), and Foundry Enablement (supporting top customers and validating technologies). The team focuses on customer-driven, end-to-end solutions with short development cycles to deliver measurable business impact across Intel's product and foundry businesses.

Posting Statement:

All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.

Position of Trust

N/A

Work Model for this Role

This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. * Job posting details (such as work model, location or time type) are subject to change.