Gauss Labs

Industrial AI for semiconductor manufacturing optimization

Forward-Deployed Site Reliability Engineer - KR

Site Reliability EngineeringConfirmed live in the last 24 hours

Full-timeSeoul, South KoreaNo salary listed

About the Job

Requirements

A bachelor's degree in computer science, engineering, or a related discipline is required.
At least five years of industry experience as a Site Reliability Engineer or in platform or infrastructure engineering is required.
Experience operating workloads on a cluster controlled by another team and communicating technical needs across that boundary is required.
Hands-on experience operating Kubernetes in production is required, including cluster lifecycle, scheduling, autoscaling, and resource management; Amazon EKS experience is preferred.
Experience with cloud platforms, preferably AWS, and containerization technologies including Docker and Kubernetes is required.
Experience with observability and alerting tools including Prometheus, Grafana, Elasticsearch, and Jaeger is required.
Experience with scripting languages including Python and Bash is required.
Working knowledge of GitHub, GitHub Actions, and continuous integration and continuous delivery concepts is required.
Strong problem-solving and troubleshooting skills are required.
Working proficiency in English for internal documentation and technical coordination is required.

Responsibilities

Own first response and the on-call rotation for the platform layer; coordinate responses in the incident channel when an internal incident spans multiple teams.
Deploy and operate Panoptes at the application-namespace level in customer-managed environments, diagnosing platform needs, communicating technical requirements to the customer infrastructure team, and operating within its setup, decisions, and constraints.
Own the platform layer end-to-end in the internal development environment, including cluster health, resource management for CPU, memory, and out-of-memory conditions, scheduling, autoscaling, and Kubernetes and EKS lifecycle.
Build and maintain monitoring and alerting for the infrastructure and platform layer to identify and resolve issues before they affect the platform.
Develop automation tools and scripts to streamline operations, reduce manual effort, and enable engineering teams to operate their services safely.
Forecast resource needs, optimize resource utilization, and ensure platform infrastructure can handle increasing workloads.
Build and maintain continuous integration and continuous delivery pipelines and deployment infrastructure for the platform.
Identify and drive improvements to platform reliability, performance, and efficiency.

Desired Qualifications

Knowledge of artificial intelligence and machine learning infrastructure and workloads.
Knowledge of database technologies including MongoDB and PostgreSQL.
Experience operating systems in environments not fully controlled by the operator, such as a customer site, on-premises environment, managed service provider, or another team's cluster.
Experience leading incidents from diagnosis through root cause.
Exposure to manufacturing, semiconductor, or enterprise business-to-business customer environments.

Gauss Labs is an industrial AI company on a mission to revolutionize manufacturing with AI, starting with the semiconductor sector. Panoptes is an AI-based process intelligence solution deployed in high-volume manufacturing fabs, helping customers improve yield, reduce costs, and accelerate production. Our software runs in our customers’ own managed environments. As our Site Reliability Engineer, you are the first responder for the platform layer that Panoptes runs on in production at the customer site, and you own its on-call rotation. You won’t control the cluster/node layer; your job is to diagnose what the platform needs, make the case to the customer’s infrastructure team, and keep the platform reliable within their constraints. You will also own monitoring and alerting for the platform layer, and build the automation and observability that reduce operational toil and speed up incident response.

Responsibilities

Incident Response and On-call: Own first-response and the on-call rotation for the platform layer. Alerts are routed to the owning team and when an internal incident spans more than one team, this role coordinates the response in the incident channel.
Customer-environment operations and technical communication: Deploy and operate Panoptes at the application-namespace level in the customer-managed environment. The cluster, node, and Kubernetes layer is controlled by the customer’s infrastructure team: diagnose what the platform needs, make the technical case to that team, and operate within their setup, decisions, and constraints.
Internal cloud (AWS) environment: Own the platform layer end-to-end in our internal development environment — cluster health, resource management (CPU/memory/OOM), scheduling, autoscaling, and Kubernetes/EKS lifecycle.
Monitoring and Alerting: Build and maintain robust monitoring and alerting for the infrastructure and platform layer to proactively identify and resolve issues before they impact the platform.
Automation: Develop automation tools and scripts to streamline operations, reduce manual effort, and enable engineering teams to operate their own services safely.
Capacity Planning: Forecast resource needs, optimize resource utilization, and ensure the platform infrastructure can handle increasing workloads.
Deployment infrastructure: Build and maintain CI/CD pipelines and deployment infrastructure for the platform.
Continuous Improvement: Drive a culture of continuous improvement by identifying opportunities to enhance platform reliability, performance, and efficiency.

Basic Qualifications

Bachelor's degree in computer science, engineering, or a related discipline
5+ years of industry experience as a Site Reliability Engineer or in platform/infrastructure engineering
Experience operating workloads on a cluster controlled by another team, and communicating technical needs across that boundary
Hands-on experience operating Kubernetes in production (EKS preferred): cluster lifecycle, scheduling, autoscaling, resource management
Experience with cloud platforms (AWS preferred) and containerization technologies (Docker, Kubernetes)
Experience with observability and alerting tools (Prometheus, Grafana, ElasticSearch, Jaeger)
Experience with scripting languages (Python, Bash)
Working knowledge of GitHub, GitHub Actions, and CI/CD concepts
Strong problem-solving and troubleshooting skills
Working proficiency in English for internal documentation and technical coordination

Preferred Qualifications

Knowledge of AI/ML infrastructure and workloads.
Knowledge of database technologies (MongoDB, PostgreSQL)
Experience operating systems in an environment you didn’t fully control — a customer site, on-prem, an MSP, or another team’s cluster
Experience leading incidents from diagnosis through root cause
Exposure to manufacturing, semiconductor, or enterprise B2B customer environments

[Interview process]

Application reivew - Phone interview - Virtual onsite interview - VP interview/Core Value interview - CEO interview

About the Company

Gauss Labs

Industrial AI for semiconductor manufacturing optimization

Gauss Labs builds AI-powered software for manufacturing, with a focus on the semiconductor sector. Its products monitor and optimize factory processes by collecting machine-generated data from production lines and running AI models on scalable software infrastructure to detect anomalies, improve quality, and reduce downtime. The company differentiates itself through deep domain expertise in industrial AI, a leadership team with a background in enterprise ML and product development, and a cross‑border presence in Silicon Valley and Seoul to serve large manufacturing customers with enterprise-grade solutions. The goal is to make semiconductor factories more efficient and reliable by turning data into actionable insights and automated process improvements.

Company size: 51-200
Company stage: Late Stage VC
Total funding: $55M
Headquarters: Palo Alto, CA
Founded: 2020

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