ChipStack
About Us
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.
About This Role This role offers a unique opportunity to be part of the founding team at ChipStack, where we are reinventing how modern silicon chips are designed. You will work alongside highly experienced chip designers, ML scientists, and top‑notch infrastructure and software engineers. You will leverage your experience building ML and data infrastructure and apply it to some of the hardest problems in chip design.
About You You want to be at a startup because you love to be at the center of all the dynamism that a startup offers. You are willing to put in the hours and go the extra mile to ensure every customer has an exceptional experience. You are self‑motivated with a sense of urgency and can operate independently without much guidance. You are not afraid of difficult problems and enjoy venturing into areas you have not explored before.
Responsibilities We’re looking for a strong, experienced ML Infrastructure Engineer to join our founding team. You’ll be responsible for building the core infrastructure that enables training, fine‑tuning, evaluation, and deployment of LLMs across cloud and on‑premise environments. Your work will directly impact product capabilities and speed of iteration.
Qualifications
5+ years of experience in ML infrastructure or adjacent roles
Deep expertise in Python and experience with training frameworks like PyTorch or TensorFlow
Strong systems engineering skills and experience with distributed training, data pipelines, and performance optimization
Experience deploying ML models to production (REST APIs, batch jobs, streaming pipelines)
Proficiency with cloud platforms (e.g., GCP, AWS) and containerized systems (Docker, Kubernetes)
Experience managing GPU/TPU workloads efficiently
Good communication skills and the ability to work directly with engineers and customers
Prior experience training or fine‑tuning LLMs
Experience setting up observability, monitoring, and evaluation pipelines for ML models
Nice to Have
Exposure to chip design fundamentals (via coursework or elsewhere)
Experience at an early‑stage startup
Company Culture Challenge status‑quo: We are innovators who can challenge the status quo and 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 are always open to learning.
Ship fast, ship quality: We ruthlessly prioritize what matters. We build a few things, but 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.
Seniority Level Mid‑Senior level
Employment Type Full‑time
#J-18808-Ljbffr
About This Role This role offers a unique opportunity to be part of the founding team at ChipStack, where we are reinventing how modern silicon chips are designed. You will work alongside highly experienced chip designers, ML scientists, and top‑notch infrastructure and software engineers. You will leverage your experience building ML and data infrastructure and apply it to some of the hardest problems in chip design.
About You You want to be at a startup because you love to be at the center of all the dynamism that a startup offers. You are willing to put in the hours and go the extra mile to ensure every customer has an exceptional experience. You are self‑motivated with a sense of urgency and can operate independently without much guidance. You are not afraid of difficult problems and enjoy venturing into areas you have not explored before.
Responsibilities We’re looking for a strong, experienced ML Infrastructure Engineer to join our founding team. You’ll be responsible for building the core infrastructure that enables training, fine‑tuning, evaluation, and deployment of LLMs across cloud and on‑premise environments. Your work will directly impact product capabilities and speed of iteration.
Qualifications
5+ years of experience in ML infrastructure or adjacent roles
Deep expertise in Python and experience with training frameworks like PyTorch or TensorFlow
Strong systems engineering skills and experience with distributed training, data pipelines, and performance optimization
Experience deploying ML models to production (REST APIs, batch jobs, streaming pipelines)
Proficiency with cloud platforms (e.g., GCP, AWS) and containerized systems (Docker, Kubernetes)
Experience managing GPU/TPU workloads efficiently
Good communication skills and the ability to work directly with engineers and customers
Prior experience training or fine‑tuning LLMs
Experience setting up observability, monitoring, and evaluation pipelines for ML models
Nice to Have
Exposure to chip design fundamentals (via coursework or elsewhere)
Experience at an early‑stage startup
Company Culture Challenge status‑quo: We are innovators who can challenge the status quo and 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 are always open to learning.
Ship fast, ship quality: We ruthlessly prioritize what matters. We build a few things, but 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.
Seniority Level Mid‑Senior level
Employment Type Full‑time
#J-18808-Ljbffr