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AlgorithmFull-timeLocation：Shenzhen

LLM Algorithm Engineer

Research deep learning algorithms for the sports & health foundation model — fine-tune, optimize, and ship AI capabilities into real business scenarios.

ShenzhenTeam：Algorithm
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Responsibilities

  • Tackle specific problems in the sports & health foundation model direction; collaborate with sports-science and product teams to define task pipelines, collect or build high-quality datasets, and fine-tune models.
  • Explore specific applications via prompt engineering, model fine-tuning, and tool/plugin invocation; design and optimize models for business scenarios, including multimodal understanding, object detection, and segmentation.
  • Master fine-tuning and optimization of large neural networks (including but not limited to BERT, GPT); adjust and improve models across tasks and datasets to lift real-scenario performance.
  • Improve the model's sports & health capabilities, including but not limited to efficient training, human-feedback alignment, multimodality, controllable text generation, and generation-quality evaluation.
  • Design and implement end-to-end ML and deep learning algorithms that connect models to real business needs, covering NLP, recommendation systems, and more.
  • Define and execute the foundation-model algorithm strategy, including technical roadmap planning, team building, and project management, aligned with company strategy.
  • Work closely with product and business teams to understand requirements and logic, and land AI technology in real scenarios to deliver business value.
  • Track the latest research in AI foundation models and apply it to real projects.

Requirements

  • Full-time Master's degree or above in CS, machine learning, reinforcement learning, pattern recognition, AI, or related fields.
  • Experience fine-tuning and optimizing deep learning models; familiar with mainstream models/algorithms and large neural network architectures and optimization techniques.
  • Solid programming foundation; proficient in Python, C++, etc.; familiar with PyTorch, TensorFlow, and other deep learning frameworks.
  • Solid ML/DL theory; familiar with Transformer, BERT, and other common architectures.
  • Familiar with AI frameworks such as LangChain; able to build AI applications with LangChain-like tooling.
  • Strong communication, logical analysis, self-drive, self-learning, and stress tolerance; high sense of responsibility and teamwork.
  • Solid math and ML theory; able to understand and apply various ML/DL algorithms.
  • Strong interest in AI and data science; eager to learn and explore new technologies; maintain technical acuity and innovation.
  • Excellent English (listening/speaking) is a plus; experience with Agent projects is a plus.
Send your résumé to career@speediance.com
LLM Algorithm Engineer | Speediance