Senior AI Engineer (Applied)
Razer is hiring a Senior AI Engineer (Applied) in Singapore, Singapore. Level rates it ; you can apply on Razer.
Level's read on this job
- Builds AI ●●●● is how Level rates this AI engineer role: the job is building AI systems.
- Tools and skills the posting cites include RAG, AI agents and computer vision.
- Level classifies it as a senior role.
- Level lists 148 other open roles at Razer.
AI in this role
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?
How we rate this
Senior AI Engineer (Applied) at Razer rates 98 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Pay
- Typical AI engineer job
- $184k
This posting doesn't list pay. Use the typical AI engineer figure when pay comes up. See AI engineer jobs
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Walk me through a computer vision problem you solved, from raw data to a deployed model.
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- How would you decide a model or AI system is ready to ship?
Adapt your resume
- List these exact terms on your resume: RAG, AI agents, Computer vision, and NLP. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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