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Razer

Develops gaming hardware, software, and peripherals

AI Software Engineer

Applied Machine LearningUpdated on Nov 12
Full-timeSingaporeNo salary listed

About the Job

Requirements

  • At least 3 years of experience in AI/ML software development.
  • A proven track record of deploying AI solutions in production environments.
  • Strong experience deploying AI models and developing APIs using RESTful APIs, gRPC, or edge computing solutions.
  • Strong programming skills in Python, Java, or C++.
  • Hands-on experience with TensorFlow, PyTorch, and Scikit-learn.
  • In-depth understanding of containerization with Docker and Kubernetes and of DevOps practices.
  • Experience developing and deploying AI applications for edge deployment using TensorRT, ONNX, or TFLite, and on cloud infrastructure such as AWS, Azure, or Google Cloud Platform, using infrastructure-as-code tools such as Terraform and cloud AI services such as AWS SageMaker, Google Vertex AI, or Azure ML.
  • Experience with database management, including SQL, NoSQL, and vector databases.
  • Knowledge of distributed computing with Spark or Dask and parallel processing.
  • Ability and willingness to learn and apply new technologies in a fast-paced, high-pressure, agile environment.
  • Excellent written and verbal communication skills for coordinating across teams.
  • A Bachelor's or Master's degree in computer science, AI, or a similar discipline from an accredited institution.

Responsibilities

  • Implement and optimize AI/ML models in production through containerization with Docker and Kubernetes, targeting speed, accuracy, and cost-effectiveness.
  • Deploy AI models using RESTful APIs, gRPC, or edge computing solutions.
  • Implement monitoring, logging, and error-handling mechanisms to track AI performance.
  • Design secure, performant, and well-documented APIs and microservices to integrate AI capabilities into software systems.
  • Monitor and optimize model performance in production environments, ensuring API latency and availability meet required service-level agreements.
  • Build scalable, high-performance AI pipelines for real-time and batch processing.
  • Implement MLOps best practices, including CI/CD for machine-learning workflows on local machines and cloud platforms.
  • Work with data scientists to turn research models into deployable solutions.
  • Collaborate with DevOps and cloud engineers to ensure seamless AI model deployment.
  • Keep up to date with AI/ML frameworks, tools, and industry trends in API and plugin development to improve AI API solutions.
  • Identify opportunities to improve existing AI API and plugin architectures and suggest new features or services for AI products.

About the Company

Razer

Develops gaming hardware, software, and peripherals

Razer designs and sells gaming hardware and software for gamers and tech enthusiasts. Its products include laptops, desktops, monitors, mice, keyboards, audio devices, and chairs, plus software such as Chroma RGB that customizes lighting and optimizes performance. It differentiates itself with an integrated hardware-software ecosystem, esports sponsorships, and direct-to-consumer sales. Its goal is to be a leading global gaming brand by expanding its hardware-software ecosystem and presence in gaming communities.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Irvine, CA
Founded
1998

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