AI Engineer, Multimodal Systems
Razer Open · verified Oct 22, 2026 At a glance
Mid-level AI Engineering role at Razer. France · full-time · no salary stated · we estimate €47,375–€61,000 across France.
Razer has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Build AI systems that recognize in-game events using video and audio, and tune models for efficiency
- Create computer vision and audio workflows that generate datasets and apply labels automatically
- Train, test and deploy models for games across the stated top-game tiers
- Filter out irrelevant gameplay footage through a video decluttering pipeline
- Write C++ modules for data capture, inference and serving, then optimize on-device latency with SDK developers
What you bring
- You’re proficient in C++ for performance-focused implementation
- You understand machine learning foundations such as CNNs, transformers and multimodal fusion
- You’ve integrated models with OpenCV, PyTorch or TensorFlow
- You bring computer vision or audio event classification experience, plus familiarity with dataset labeling and real-time deployment
Who this fits
This mid-level role suits an AI engineer focused on multimodal game-event detection, dataset pipelines and efficient on-device inference. You’ll work closely with a Lead Engineer and SDK developers. The role is based in France.
From the employer
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 :
Designs and implements AI components for in-game event recognition, multimodal learning, and model optimization. Develops CV and audio processing pipelines for automated dataset generation and labeling. Collaborates on training workflows for the top 100, 500, and 3000 games. Builds the video decluttering pipeline to filter irrelevant gameplay segments. Works closely with the Lead Engineer on model deployment optimization and SDK integration. Implements and maintains C++ modules for data acquisition, inference, and model serving. Focused on performance tuning and inference latency reduction for on-device intelligence.Mission:
Develop and optimize AI components for multimodal in-game event recognition, video dataset generation, and model deployment.
- Build AI modules for CV/audio-based in-game event detection.
- Implement data preprocessing and feature extraction pipelines.
- Train, validate, and deploy models across top 100–3000 games.
- Design video decluttering pipeline for gameplay quality refinement.
- Collaborate with SDK developers for on-device inference optimization.
- Ensure low-latency, high-accuracy inference performance.
Competencies:
- Applied AI engineering and model lifecycle understanding.
- Multimodal data processing (video, audio, metadata).
- Rigorous analytical and debugging skills in performance-critical contexts.
- Systematic approach to scalability, reproducibility, and deployment.
Pre-Requisites :
- Proficient in C++ for high-performance implementation.
- Solid understanding of ML fundamentals (CNNs, transformers, multimodal fusion).
- Experience with OpenCV, PyTorch, or TensorFlow for model integration.
- Background in computer vision or audio event classification.
- Familiarity with dataset management, labeling, and augmentation techniques.
- Experience with real-time inference and model compression for deployment.
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?