AI/ML Engineer

• Design and develop event detection models that can be universally applied across various games.
• Leverage existing open-source models or design and train custom models as needed.
• Develop vision-based models to identify important moments in gameplay videos.
• Optimize and compress models for on-device environments.
• Improve models considering not only accuracy but also latency, memory, CPU/GPU usage, and stability.
• Increase robustness to handle diverse games, resolutions, UIs, and PC specs in the production environment.
• Collaborate with engineers to integrate models into the product and validate them in real user environments.
• Solve problems end-to-end -- from data collection using 200 million monthly video data points, labeling strategies, training pipelines, to evaluation criteria.

• DOR builds products that customers want, not products the CEO wants.
• We repeat problem definition, hypothesis, execution, measurement, and learning in short 1-2 week iterations.
• AI/ML Engineers are not just researchers -- they solve real product problems.
• We build fast, validate fast, and adjust direction fast.
• We focus on creating real impact based on data and user feedback.
• We value results that connect not only to performance metrics but also to user experience.

We don't expect experience with every stack. However, we expect you to learn and pick things up quickly.

• 2+ years of experience in AI/ML or related software development
• Experience directly developing and training Computer Vision or deep learning models
• Ability to go beyond using open-source models to tune or redesign them for specific problems
• Experience with model optimization for on-device or edge environments, or strong interest in this area
• Ability to consider not only accuracy but also latency, resource usage, and robustness
• Desire to technically solve real product problems with actual users
• Tenacity to dig deep into difficult problems and solve them

• Able to work in San Francisco, CA / United States
• Experience working with game footage, broadcast video, or user interaction video
• Experience with image classification, detection, temporal modeling, or event detection
• Experience with inference optimization using ONNX, TensorRT, OpenVINO, etc.
• Experience with model compression, quantization, pruning, or distillation
• Experience measuring and improving model performance on actual devices
• Experience with dataset design, labeling strategies, and training pipeline construction
• Experience integrating with Windows environments or desktop applications
• Experience with video processing, social media, or UGC products
• A gamer or someone with deep understanding of gameplay context

• Someone deeply interested in creating real product impact
• Someone who doesn't stop at paper implementations but makes things work end-to-end in real environments
• Someone who enjoys solving trade-offs between accuracy and system performance
• Someone who rapidly improves even with imperfect data and complex real-world conditions
• Someone who wants to build AI features that gamers worldwide use every day

• Tell us what AI/ML problems you've solved and what impact you've made.
• If you have experience leveraging open-source models or designing your own to solve problems, please share.
• If you have experience improving model accuracy, latency, memory usage, or inference speed, please describe in detail.
• If you have experience integrating and operating models in production or device environments, please share.
• If you have end-to-end experience from data collection, labeling, training, evaluation, to deployment, please describe.
• Rather than listing work history and credentials, we'd love to see your problem definition, thought process, actions, learnings, and outcomes.

The entire hiring process is completed within 7 days. During intensive hiring periods, we'll reach out quickly at each stage.