Descrizione dell'offerta
Department Introduction
The SSD ASIC Architecture team defines the end‑to‑end architecture of next‑generation SSD controller ASICs. We translate product and customer requirements into scalable, high‑performance architectures spanning PCIe/NVMe, NAND and memory subsystems, security, power, and cost. Working closely with Firmware, Design, Verification, and Technology teams, we drive architectural consistency, reuse, and innovation from concept through tape‑out and silicon enablement.
Role Summary
This internship focuses on developing AI‑enabled engineering assistants integrated with existing tools and workflows. The intern will support an architecture‑driven solution where capabilities are implemented as modular, composable “tool + skill” components rather than a single monolithic chatbot. The role blends software engineering, applied AI, and close collaboration with engineering teams.
Responsibilities
- Collaborate with engineers to understand recurring workflow challenges and usability needs.
- Design and implement small, composable AI modules (“tools” and “skills”) that perform focused tasks and can be orchestrated into larger workflows.
- Integrate assistants with existing engineering tools, data sources, and documentation using approved patterns.
- Validate correctness and robustness of analysis through test cases, reviews, and feedback loops.
- Document module behavior, assumptions, and usage guidelines for internal users.
- Participate in design reviews and iterative improvements based on real engineering feedback.
Minimum Qualifications
- Currently pursuing a degree in Computer Engineering, Electrical Engineering, Computer Science, or a related field.
- Proven understanding of AI/ML fundamentals, including modern GenAI concepts such as LLMs and embeddings.
- Programming skills in Python, JavaScript and/or C/C++; familiarity with Linux environments.
- Proven problem‑solving and debugging skills.
- Ability to communicate clearly and collaborate in a cross‑functional engineering setting.
Preferred Qualifications
- Exposure to hardware/software codesign, verification, simulation, firmware, or debug workflows.
- Experience with LLM tooling/agent frameworks, prompt engineering, or building developer productivity tools.
- Familiarity with retrieval‑augmented generation (RAG), including vector search, grounding techniques, building, and integrating backend services (REST APIs).
- Experience with agentic/LLM orchestration frameworks (e.g., LangChain, LangGraph) or equivalent.
- Familiarity with enterprise software practices such as access control, validation, and documentation.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
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