WHELFS TALENT GROUP
Large Model Algorithm Expert
Source: | Author:x | Published time: 2026-09-16 | 28 Views | 🔊 Click to read aloud ❚❚ ▶ | Share:
artificial intelligence company · Nanshan District, Shenzhen · Shenzhen

Job Details

About the Company: A high-tech company specializing in artificial intelligence. It is recruiting overseas high-level talent across Large Model Algorithm Expert, Perception Algorithm Expert and related areas.

Target Candidates: Overseas PhDs or senior algorithm experts in AI, large language models, multimodal algorithms, and machine learning engineering

Responsibilities

    •  Develop and optimize the deep-learning system toolchain, implement end-to-end automated workflows for model training, quantization, conversion, and testing, and accelerate the translation of algorithms from research to deployment.

    •  Develop end-to-end autonomous-driving models, design model architectures and multi-task supervision strategies, and generate ego-vehicle decisions from raw sensor data.

    •  Responsible for developing end-to-end autonomous-driving models, able to design model architectures and multi-task supervision, and output ego-vehicle decisions from raw sensor information.

    •  Participate in the development of automated data pipelines and model evaluation, continuously iterating to improve end-to-end model performance.

Requirements

    •  Experience training multimodal or large language models.

    •  Familiarity with mainstream large-model training methods and proficiency in a range of fine-tuning techniques.

    •  Familiar with mainstream perception, prediction, and decision-planning algorithms, with relevant development experience.

    •  PhD-level training or equivalent senior technical expertise in a relevant field.

    •  Relevant expertise in AI, large language models, multimodal algorithms, and machine learning engineering.

Highlights & Support: This recruitment covers approximately 20 positions with compensation of RMB 500K–1M/year. Specific position level, compensation, and support terms can be further negotiated based on the candidate's academic background, project experience, commercialization achievements, and interview results.