Senior AI Engineer (Applied)

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

Qualifications

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

Familiarity with containerization and orchestration tools (Docker, Kubernetes)

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 :

Razer is proud to be an Equal Opportunity Employer. We believe that diverse teams drive better ideas, better products, and a stronger culture. We are committed to providing an inclusive, respectful, and fair workplace for every employee across all the countries we operate in. We do not discriminate on the basis of race, ethnicity, colour, nationality, ancestry, religion, age, sex, sexual orientation, gender identity or expression, disability, marital status, or any other characteristic protected under local laws. Where needed, we provide reasonable accommodations - including for disability or religious practices - to ensure every team member can perform and contribute at their best.

Are you game?