Founding AI / Data Engineer (Semantic Systems)
Role summary
MachAI Lens is seeking a Founding AI / Data Engineer to build their Unstructured Data Engine, transforming messy engineering data (logs, notes) into a high-fidelity data layer. This role involves developing LLM-driven parsers to extract insights from EDA log files, scaling RAG pipelines with vector databases like Pinecone or Weaviate, and implementing Explainable AI (XAI) for trust. The ideal candidate has 3-5+ years of experience building production-grade AI/data pipelines, deep knowledge of LLM orchestration tools (LangChain, LlamaIndex), and a passion for tackling complex data challenges in the semiconductor industry. This is a unique opportunity to be a founding architect in a startup environment backed by established industry expertise.
The Challenge:
In chip design, the most critical "why" is often buried in a 100,000-line log file or a frantic Slack thread between teams. This "dark data" is currently invisible to tools.
MachAI Lens is bringing it into the light.
The Mission:
You are the architect of our
Unstructured Data Engine
. Your goal is to turn the "messy" reality of engineering—logs, notes, and memos—into a high-fidelity, correlated data layer. You will build the RAG pipelines that allow a Program Manager to ask,
*"Why did our PCIe block regress?"*
and get a physics-backed answer in seconds.
What You’ll Do:
- You will be a Founding AI / Data Engineer
- Build the "Needle-Finder":
Develop LLM-driven parsers capable of extracting critical insights from massive, unstructured EDA log files and correlating them to specific silicon coordinates.
- Scale RAG Pipelines:
Design and deploy high-performance
Vector Database
architectures (Pinecone/Weaviate) that can handle the sheer volume of semiconductor project data.
- Ensure AI Trust:
Implement
Explainable AI (XAI)
frameworks. When our agent suggests a fix, it must provide the "reasoning log" so engineers can verify the logic.
- Cross-Domain Innovation:
Collaborate with timing experts to map human-written "intent" to structured hardware metrics.
What You Bring:
- Education:
A Bachelor’s degree in Computer Science, Data Science, or Software Engineering.
- Data Experience:
3–5+ years building production-grade AI or data pipelines. You know that
Data Cleaning
is where the real magic happens.
- AI Toolbelt:
Deep experience with
LangChain, LlamaIndex
, and modern LLM orchestration.
- Curiosity:
You aren't afraid of "dirty data." You enjoy the challenge of finding patterns where others see noise.
Why Join MachAI? We are at the intersection of two massive worlds: the 15-year established expertise of Advance Micro Consulting Inc. (AMCI) and the "0-to-1" energy of an AI-native startup. Most startups have a "runway" problem; we have a "pedigree" advantage.
Joining us means you aren't just a cog in a legacy machine. You are a founding architect of a platform designed to solve the most frustrating "unsolvable" problem in semiconductors—the data paradox.
Employment Note: This role is part of the MachAI founding team. For payroll, benefits, and government R&D compliance (including IRAP), the legal employer of record is our parent firm, Advance Micro Consulting Inc. (AMCI). You get the upside of a 0-to-1 AI startup with the 15-year stability of an industry leader.