ChipStack
About ChipStack
Chips are at the center of today's tech‑driven world. But how we design them has not changed in decades, while their complexity and specialization have skyrocketed due to increasing performance demands from applications like AI. We want to change that.
Our team is small, technical, and fast‑moving. We’ve built and shipped at the intersection of AI, EDA, and systems software, with deep roots at companies like Qualcomm, Nvidia, Google, Meta, and the Allen Institute for AI. We’re backed by top investors including Khosla Ventures, Cerberus, and Clear Ventures, and already deployed with 10+ innovative customers—from Fortune 100s to cutting‑edge AI silicon startups.
Role Overview You’ll design, engineer, and research agentic systems—software that plans, executes, uses tools, and learns. You’ll bridge LLM agent research (prompting, tool use, memory architectures) with the engineering that puts these systems in production for chip design workflows.
Key Responsibilities Agent Research & Prototyping
Architect and iterate on agentic components: memory, context engineering, tool usage, multi‑agent coordination
Experiment with prompting, finetuning, and orchestration to improve agent performance
Infrastructure Development
Build scalable infrastructure for prompt iteration / testing, benchmarking, logging, and evaluation
Assist with pipelines for fine‑tuning, automated evaluation, and model deployment
Collaboration & Integration
Work directly with chip designers and ML infra engineers to embed agentic workflows into chip design pipelines
Partner with product teams to solve core agent challenges (e.g., long‑horizon planning, tool integration)
Research & Metrics
Define and evaluate performance metrics for agent systems
Design goal‑oriented agentic workflows to enhance task completion
You Should Have
5+ years of combined ML research and / or software engineering experience
Hands‑on with LLMs: prompting, finetuning, evaluation
Strong programming skills
Solid foundations in distributed systems, data pipelines
Cloud + on‑premise infra experience involving GPUs; familiarity with Docker
Excellent communication & a bias toward collaborative problem‑solving
PhD or MS in ML, CS, or related field, or equivalent research + implementation experience
Ability to build, evaluate, and iterate LLM‑based applications
Nice‑to‑Have
Experience in fine‑tuning LLMs specifically for agentic applications
Experience designing agentic systems or multi‑agent workflows
Familiarity with reinforcement learning (RLHF / RL‑agent contexts)
Background in integrated ML infra and agent evaluation pipelines
Interest or experience in the chip design / EDA domain
What Makes This Role Unique
Play a key role at the intersection of agent research and real‑world infra, delivering autonomous workflows for chip design
Influence both the research direction and the productionization of agentic systems
Join a tight‑knit founding team, directly impacting high‑stakes chip‑design automation tasks
Culture
Challenge status quo: we are innovators who can push forward our vision of the world
Strong opinions, loosely held: we are low on ego, but high on collaboration; we are okay to be wrong and always open to learning
Ship fast, ship quality: we ruthlessly prioritize what matters, building a few things at lightning speed with high quality
Proud of our craft: attention to detail is in our DNA; we take pride in what we build and ensure they exceed the high standards of the semiconductor industry
#J-18808-Ljbffr
Chips are at the center of today's tech‑driven world. But how we design them has not changed in decades, while their complexity and specialization have skyrocketed due to increasing performance demands from applications like AI. We want to change that.
Our team is small, technical, and fast‑moving. We’ve built and shipped at the intersection of AI, EDA, and systems software, with deep roots at companies like Qualcomm, Nvidia, Google, Meta, and the Allen Institute for AI. We’re backed by top investors including Khosla Ventures, Cerberus, and Clear Ventures, and already deployed with 10+ innovative customers—from Fortune 100s to cutting‑edge AI silicon startups.
Role Overview You’ll design, engineer, and research agentic systems—software that plans, executes, uses tools, and learns. You’ll bridge LLM agent research (prompting, tool use, memory architectures) with the engineering that puts these systems in production for chip design workflows.
Key Responsibilities Agent Research & Prototyping
Architect and iterate on agentic components: memory, context engineering, tool usage, multi‑agent coordination
Experiment with prompting, finetuning, and orchestration to improve agent performance
Infrastructure Development
Build scalable infrastructure for prompt iteration / testing, benchmarking, logging, and evaluation
Assist with pipelines for fine‑tuning, automated evaluation, and model deployment
Collaboration & Integration
Work directly with chip designers and ML infra engineers to embed agentic workflows into chip design pipelines
Partner with product teams to solve core agent challenges (e.g., long‑horizon planning, tool integration)
Research & Metrics
Define and evaluate performance metrics for agent systems
Design goal‑oriented agentic workflows to enhance task completion
You Should Have
5+ years of combined ML research and / or software engineering experience
Hands‑on with LLMs: prompting, finetuning, evaluation
Strong programming skills
Solid foundations in distributed systems, data pipelines
Cloud + on‑premise infra experience involving GPUs; familiarity with Docker
Excellent communication & a bias toward collaborative problem‑solving
PhD or MS in ML, CS, or related field, or equivalent research + implementation experience
Ability to build, evaluate, and iterate LLM‑based applications
Nice‑to‑Have
Experience in fine‑tuning LLMs specifically for agentic applications
Experience designing agentic systems or multi‑agent workflows
Familiarity with reinforcement learning (RLHF / RL‑agent contexts)
Background in integrated ML infra and agent evaluation pipelines
Interest or experience in the chip design / EDA domain
What Makes This Role Unique
Play a key role at the intersection of agent research and real‑world infra, delivering autonomous workflows for chip design
Influence both the research direction and the productionization of agentic systems
Join a tight‑knit founding team, directly impacting high‑stakes chip‑design automation tasks
Culture
Challenge status quo: we are innovators who can push forward our vision of the world
Strong opinions, loosely held: we are low on ego, but high on collaboration; we are okay to be wrong and always open to learning
Ship fast, ship quality: we ruthlessly prioritize what matters, building a few things at lightning speed with high quality
Proud of our craft: attention to detail is in our DNA; we take pride in what we build and ensure they exceed the high standards of the semiconductor industry
#J-18808-Ljbffr