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FuriosaAI

Power-efficient AI inference accelerator chips

Production Operation Engineer

Machine & Process OperationConfirmed live in the last 24 hours
Full-timeSeoul, South KoreaNo salary listedIn-person

About the Job

Requirements

  • Three to five years of practical experience in system operations, data analysis, or process improvement.
  • Ability to understand production or testing workflows, operate existing systems reliably, and analyze problems.
  • Ability to write, modify, and maintain production-operation programs and scripts using Python or Bash.
  • Ability to inspect files, logs, processes, and execution status in Linux and investigate test failures.
  • Ability to collect and validate data and explain causes and improvement directions based on changes in yield, defect rates, and test results.
  • Ability to manage program change and deployment history and execution conditions, and document operating guides and incident response procedures.
  • Ability to clearly communicate and resolve operational issues with manufacturing partners and internal departments.

Responsibilities

  • Understand production flows and test procedures, and check the operational status of production management frameworks and test environments.
  • Verify products, test equipment and servers, program versions, and configurations, and monitor progress and failures at each production stage.
  • Clarify operating procedures so production-floor teams can work to consistent standards and report abnormalities.
  • Develop programs for production equipment and board control, test execution, result collection, data validation, and reporting, and modify existing code.
  • Use Python and Bash to automate repetitive work and improve operational problems caused by insufficient logging or exception handling.
  • Coordinate with software engineers on shared framework functions used for evaluations and production tests, and apply and maintain those functions in line with production-line procedures and interfaces.
  • Check execution conditions, inputs and outputs, and result formats for new or modified programs, and assess their effects on existing production flows.
  • Review test results before application and verify normal operation and error trends after deployment on site.
  • Manage deployed versions, configuration histories, usage instructions, and recovery procedures so issues can be traced and operations restored.
  • Collect and validate production yield, defect rates, test success rates, and test logs, and compare differences by product, version, equipment, and production conditions.
  • Investigate whether failures originate from product defects, equipment issues, environment settings, or program errors.
  • Resolve operational issues on site and provide relevant data and reproduction conditions to quality and development personnel when product or validation-logic analysis is needed.
  • Identify causes of recurring errors and delays and improve test procedures, programs, and reporting flows.
  • Provide technical support to manufacturing partners on questions and operational issues, and communicate changed procedures and precautions.
  • Produce production-operation guides, production programs and deployment histories, incident-response records, and production-data reports.

Desired Qualifications

  • Experience in mass-production operations or technical support for semiconductor, server, or hardware products.
  • Experience in production management, production engineering, quality management, or test operations.
  • Experience developing or operating production management systems, Linux-based test environments, and automation systems.
  • Experience querying and analyzing production data using SQL and databases.
  • Experience analyzing production yield and defect data to improve processes, testing, or operating procedures.
  • Experience operating production-program deployments, version control, error handling, and recovery procedures.

About the Company

FuriosaAI

Power-efficient AI inference accelerator chips

FuriosaAI develops AI accelerators for data centers. Its flagship RNGD chip is a power-efficient accelerator designed to boost performance per watt for running large language models and other demanding AI workloads. The hardware is configurable with multiple processing elements to fit different workloads, and it is paired with advanced compiler technology and profiling tools to identify bottlenecks and optimize efficiency. This combination of flexible hardware and software optimization differentiates FuriosaAI from competitors, focusing on maximizing performance while keeping energy use low. The company targets data centers and enterprises that need high-performance, energy-efficient AI solutions, and aims to make AI computing more sustainable and scalable by selling its chips and related software tools and pursuing long-term contracts with large-scale customers.

Company size
201-500
Company stage
Series D
Total funding
$880.8M
Headquarters
Seoul, South Korea
Founded
2017

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