25 days
72 Algorithms Jobs - October 2026 - Urgent Hiring
Showing 72 jobs results for
"algorithms"
- Design of Reward Models: In the RL process, designing an effective reward model is crucial. It must accurately reflect the effectiveness of the reasoning process and guide the model to iteratively improve its reasoning ability. This involves not only setting appropriate evaluation criteria across different tasks, but also ensuring the reward model to adapt dynamically during training to match the evolving model performance.
7 days
- Design of Reward Models: In the RL process, designing an effective reward model is crucial. It must accurately reflect the effectiveness of the reasoning process and guide the model to iteratively improve its reasoning ability. This involves not only setting appropriate evaluation criteria across different tasks, but also ensuring the reward model to adapt dynamically during training to match the evolving model performance.
29 days
- Co-create with the team: Creativity is at the core of TikTok. Whether it's building the product or shaping the team, we strive to spark imagination and deliver impact — for ourselves, the platform, the communities we serve, and society as a whole.
8 days
- Co-create with the team: Creativity is at the core of TikTok. Whether it's building the product or shaping the team, we strive to spark imagination and deliver impact — for ourselves, the platform, the communities we serve, and society as a whole.
30+ days
24 days
23 days
- Search LLM Foundation R&D: Build and optimize the search-domain LLM foundation, integrating search knowledge to rapidly deliver business value; develop and refine the post-training pipeline for search LLMs (ultra-long-text / colloquial-text pre-training, image-text / video multimodal representation, e-commerce product multimodal representation learning, etc.); participate in LLM inference optimization (long-context optimization, model efficiency optimization).
8 days
- Search LLM Foundation R&D: Build and optimize the search-domain LLM foundation, integrating search knowledge to rapidly deliver business value; develop and refine the post-training pipeline for search LLMs (ultra-long-text / colloquial-text pre-training, image-text / video multimodal representation, e-commerce product multimodal representation learning, etc.); participate in LLM inference optimization (long-context optimization, model efficiency optimization).
29 days
- Build prediction/uplift NN model to improve LIVE feature intelligence;
30+ days
- Build prediction/uplift NN model to improve LIVE feature intelligence;
7 days
- Build prediction/uplift NN model to improve LIVE feature intelligence;
29 days
- Build prediction/uplift NN model to improve LIVE feature intelligence;
9 days
- Build prediction/uplift NN model to improve LIVE feature intelligence;
30+ days
- Build prediction/uplift NN model to improve LIVE feature intelligence;
7 days
- Build prediction/uplift NN model to improve LIVE feature intelligence;
29 days
- Search LLM Foundation R&D: Build and optimize the search-domain LLM foundation, integrating search knowledge to rapidly deliver business value; develop and refine the post-training pipeline for search LLMs (ultra-long-text / colloquial-text pre-training, image-text / video multimodal representation, e-commerce product multimodal representation learning, etc.); participate in LLM inference optimization (long-context optimization, model efficiency optimization).
30+ days
- Participate in the optimization of ByteDance LIVE business and serve the LIVE experience of billions of global users.
7 days
- Participate in the optimization of ByteDance LIVE business and serve the LIVE experience of billions of global users.
29 days
- Participate in the optimization of ByteDance LIVE business and serve the LIVE experience of billions of global users.
29 days
- Participate in the optimization of ByteDance LIVE business and serve the LIVE experience of billions of global users.
7 days
- Participate in the optimization of ByteDance LIVE business and serve the LIVE experience of billions of global users.
29 days
- Build and optimize cross-scenario shared Foundation Models to enable unified modeling and efficient inference.
8 days
- Build and evolve the agent runtime (harness / agent loop) powering our creator / seller agents — orchestrate skills, tools, and context.
8 days
- Build and evolve the agent runtime (harness / agent loop) powering our creator / seller agents — orchestrate skills, tools, and context.
29 days
- Build and optimize cross-scenario shared Foundation Models to enable unified modeling and efficient inference.
29 days
- Build and evolve the agent runtime (harness / agent loop) powering our creator / seller agents — orchestrate skills, tools, and context.
30+ days