3+ years of experience in Applied AI, Machine Learning Engineering, or AI Systems Engineering
Ability to work in fast paced, high pressure, agile environment.
Proactive and strong communication skills with the ability to explain technical decisions to both 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
Proven 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 (API design, modular codebases, testing)
Experience building backend services for AI systems (e.g. FastAPI, NodeJS, or similar)
Experience deploying AI workloads on cloud platforms (AWS, GCP, or Azure)
Familiarity with containerization and orchestration tools (Docker, Kubernetes)
Education & Experience
Travel Requirements
Role based in Singapore office, with occasional travel (up to 1 trip per year) for conferences, research collaborations, or business meetings.
Pre-Requisites :
Are you game?
Benefits
Vision insurance
Additional Information
Joining Razer will place you on a global mission to revolutionize the way the world games. Razer is a place to do great work , offering you the opportunity to make an impact globally while working across a global team located across 5 continents. Razer is also a great place to work, providing you the unique, gamer-centric #LifeAtRazer experience that will put you in an accelerated growth, both personally and professionally.
Job Responsibilities :
We are looking for a Senior Applied AI Engineer to lead the design, evaluation, and delivery of AI solutions across AI-powered gaming and platform use cases.
In this role, you will operate at the intersection of applied machine learning, systems engineering, and product decision-making, owning end-to-end AI workflows, from experimentation and benchmarking through to system design, deployment, and iteration. You will work closely with software engineers, product managers, Data Scientist and Data Engineers to deliver scalable, reliable, production-ready AI systems. Essential Duties and Responsibilities
Own the design and execution of evaluation and benchmarking frameworks across AI/ML systems (text, vision, generative AI), including metrics, thresholds, and failure analysis covering quality, latency, reliability, and cost
Architect and develop scalable, observable AI services and reusable platforms (evaluation tools, benchmarking services, microservices) that support multiple product teams
Design and build GenAI-driven systems, including RAG pipelines and agentic workflows, optimizing for real-world constraints such as 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, GenAI, and agentic tools, providing data-backed recommendations on build vs partner vs hybrid approaches
Collaborate closely with software and data engineering teams to integrate AI systems into broader product architectures
Mentor junior engineers and interns, and communicate complex technical concepts clearly to both technical and non-technical stakeholders
Razer · Singapore