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Razer

Develops gaming hardware, software, and peripherals

Senior Applied AI Engineer

Applied Machine LearningUpdated on Nov 12
Full-timeSingaporeNo salary listed

About the Job

Requirements

  • At least 3 years of experience in Applied AI, Machine Learning Engineering, or AI Systems Engineering.
  • Ability to work in a fast-paced, high-pressure, agile environment.
  • Strong communication skills and ability to explain technical decisions to technical and non-technical stakeholders.
  • Strong foundation in machine learning evaluation, experimentation, and statistical reasoning.
  • Hands-on experience with NLP, computer vision, or generative AI systems in real-world applications.
  • Ability to design and deliver production-grade AI services under constraints such as latency, reliability, and cost.
  • Strong programming skills in Python and solid software engineering fundamentals, including API design, modular codebases, and testing.
  • Experience building backend services for AI systems, such as FastAPI, Node.js, or similar.
  • Experience deploying AI workloads on cloud platforms such as AWS, GCP, or Azure.
  • Familiarity with containerization and orchestration tools such as Docker and Kubernetes.

Responsibilities

  • Own the design and execution of evaluation and benchmarking frameworks across AI/ML systems, including text, vision, and generative AI, with metrics, thresholds, and failure analysis covering quality, latency, reliability, and cost.
  • Architect and develop scalable, observable AI services and reusable platforms, including evaluation tools, benchmarking services, and microservices, that support multiple product teams.
  • Design and build generative AI-driven systems, including retrieval-augmented generation (RAG) pipelines and agentic workflows, optimizing for performance, scalability, and operational reliability.
  • Drive best practices in experimentation, versioning, reproducibility, and service reliability across applied AI systems.
  • Partner with product managers to evaluate AI-driven features, define success criteria, and assess feasibility and trade-offs.
  • Lead technical exploration and market scanning of emerging AI, generative AI, and agentic tools, and provide data-backed recommendations on build, partner, or hybrid approaches.
  • Collaborate with software and data engineering teams to integrate AI systems into broader product architectures.
  • Mentor junior engineers and interns, and communicate complex technical concepts to technical and non-technical stakeholders.

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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