Apply

Ready to go for it?

AI Apply speeds things up—apply directly if you prefer.

FREE ACCESS
5,000–10,000 jobs/day
JobTailor Logo

See all jobs on JobTailor

Search thousands of fresh jobs every day.

Discover
  • Fresh listings
  • Fast filters
  • No subscription required
Create a free account and start exploring right away.
Razer Inc.

Senior AI Engineer

Razer Inc.

Senior AI Engineer involved in designing and shipping AI models for gaming at Razer. Collaborating with cross-functional teams and optimizing models for performance and efficiency.

Posted 6/23/2026full-time🇫🇷 FranceSeniorWebsite

Tech Stack

Tools & technologies
C++CloudPyTorch

About the role

Key responsibilities & impact
  • Design and ship local (on-device) AI models that run efficiently across gaming, biosensing, and peripheral applications.
  • 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.
  • 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.

Requirements

What you’ll need
  • 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.

Benefits

Comp & perks
  • 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.

ATS Keywords

✓ Tailor your resume
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
AI modelsmachine learningreal-time systemson-device inferenceC++model optimizationquantizationpruningperformance profilingedge deployment