Machine Learning Engineer Intern
llmda.aiJob Title
Machine Learning Engineer Intern
Role Summary
Work with the core engineering and founding team to research, design, and deploy LLM-based solutions for semiconductor and hardware design workflows. The intern will contribute to agentic AI workflows, RAG pipelines, and data pipelines that integrate with llmda.ai's platform.
Experience Level
Entry-level internship for current students or recent graduates; intended for candidates seeking practical experience in ML/AI applied to hardware design.
Responsibilities
Primary responsibilities include prototyping and implementing ML components used in hardware engineering contexts.
- Design and implement multi-agent AI workflows that evaluate and synthesize engineering artifacts.
- Develop and optimize prompt engineering, RAG pipelines, and fine-tuning approaches for LLMs in hardware-specific contexts (e.g., interpreting Verilog, SoC requirements, IP documents).
- Ingest, clean, and structure fragmented technical data for semantic processing.
- Create and monitor evaluation metrics to ensure AI output accuracy and reduce hallucinations in technical environments.
- Collaborate with software architects, front-end developers, and hardware domain experts to integrate AI features into the product.
Requirements
Focused, practical skills and familiarity with modern ML tools and workflows. Education requirements are summarized below under Education Requirements.
- Strong understanding of LLMs, NLP, and Transformer architectures.
- Proficiency in Python and hands-on experience with ML frameworks such as PyTorch or TensorFlow.
- Experience with LLM orchestration tools (for example, LangChain, LlamaIndex) and familiarity with prompt engineering.
- Comfort solving ambiguous, open-ended technical problems and iterating quickly.
- Clear written and verbal communication skills to explain technical concepts.
Nice-to-have
- Experience with multi-agent system frameworks (e.g., AutoGen, CrewAI).
- Background or interest in hardware design, VLSI, embedded systems, or EDA tools.
- Familiarity with hardware description languages such as Verilog or VHDL.
- Previous internship or project experience deploying GenAI/RAG applications to production.
Education Requirements
Currently pursuing a BS, MS, or PhD in Computer Science, Artificial Intelligence, Electrical Engineering, or a closely related technical field (enrollment as a student is expected for the internship).
About the Company
Company: llmda.ai
Headquarters: Santa Clara, CA, USA
llmda.ai builds a Generative AI-based semiconductor design platform that integrates agentic AI and semantic engines to automate hardware and chip design processes, reduce re-spins, and identify design issues early. The company focuses on AI-driven workflow optimization and customer deployments for front-end semiconductor design and verification.
