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# Senior AI Engineer

- **Company:** Razer Inc.
- **Location:** France
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Application Programming Interfaces (APIs), Artificial Intelligence, C++ (Programming Language), Profiling, Machine Learning, Tensorflow, Real Time Systems, Pytorch, ONNX (Open Neural Network Exchange) Format, TensorRT
- **Published:** September 1, 2026
- **Apply:** https://razer.wd3.myworkdayjobs.com/Careers/job/France/Senior-AI-Engineer_JR2026007554

## About the Role

* 3+ years of experience in AI/ML engineering, applied ML, or a closely related role.
 * Proficiency in C++ (required) - comfortable writing performant, maintainable code in a real-time or systems context.
 * Hands-on experience deploying machine learning models, ideally on-device / edge rather than purely cloud.
 * Familiarity with ML frameworks and runtimes (e.g. PyTorch, ONNX Runtime, TensorRT, llama.cpp / GGML, or similar).
 * Understanding of model optimization techniques (quantization, pruning, distillation) and the trade-offs they involve.
 * Strong fundamentals in performance profiling and working within constrained compute/latency budgets.

## Description

We're looking for a Senior AI Engineer to join Razer Technology Team to design and ship local (on-device) AI models that run efficiently across gaming, biosensing, and peripheral applications. You'll work at the intersection of machine learning and real-time systems - taking models from prototype to optimized, production-grade inference that runs on the player's machine and our hardware, with tight latency and resource budgets. You'll be part of a ~25-person R&D team and collaborate closely with our haptics, audio, and platform groups.

 * Implement and optimize AI/ML models for on-device inference in latency-sensitive gaming and peripheral contexts.
 * Build and integrate models that process biosignal and sensor data (e.g. from peripherals and wearables) in real time.
 * Optimize models for performance and footprint - quantization, pruning, and acceleration across CPU/GPU/NPU targets.
 * Write efficient, production-quality C++ for the runtime and inference layers of our SDK.
 * Collaborate with platform, haptics, and audio teams to expose AI capabilities to game studios through clean, well-documented APIs.
 * Profile, benchmark, and continuously improve inference speed, memory use, and energy efficiency.


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