Gauss Labs

Software Engineer (KR)

Yesterday

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In this role, you will contribute to designing, developing, and launching Manufacturing AI products such as Virtual Metrology, Image Metrology, or Inspection platforms while collaborating with other engineers and AI scientists. This position provides an exciting opportunity to work on cutting-edge AI technologies and rapidly develop impactful features and products that deliver meaningful results. We are looking for individuals passionate about driving innovation and creating high-quality, scalable services with reliability at their core. We seek entry-level candidates eager to start their careers and experienced professionals with two or more years of relevant experience. Strong technical and communication skills and a passion for user-centric product development and continuous learning are highly valued.

Responsibilities

  • Develop, deploy, and maintain scalable and reliable large-scale Manufacturing AI SW products.
  • Select and integrate appropriate libraries, tools, and infrastructure resources for development and production.
  • Track and analyze how users interact with the platform and continuously improve the user experience.
  • Contribute to technical knowledge-sharing and team growth through active learning and collaboration.
  • Take ownership of building user-focused products with a self-driven and fast execution approach.
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    Basic Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or related fields.
  • Ability to independently develop and deploy services from the ground up.Experience applying libraries, infrastructure resources, or frameworks to real-world projects.
  • Strong problem-solving skills and a commitment to user-centric product development.
  • Passion for learning and sharing knowledge within a technical team.
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    Preferred Qualifications

  • Skilled in rapid prototyping and iterative development processes.
  • Broad expertise or experience across frontend, backend, and AI domains.
  • Experience creating impactful user services in a data-driven environment using AI.
  • Fundamental and practical understanding of machine learning and deep learning concepts.
  • Experience implementing computer vision algorithms in real-world applications.
  • Expertise with Docker, Kubernetes, Github Action, Helm, Argo CD, Airflow, and Prefect.
  • Expertise with GPU-based model serving using tools such as Triton, TorchServe, TensorFlow Serving, Kubeflow, or ONNX to enable scalable AI model deployment.
  • Experience developing and managing microservices architecture (MSA) in a Kubernetes-based cloud environment.
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