Senior AI Algorithm Engineer (Bio-genetics Synthetic Biology)

Job Description:

Responsibilities:

Lead the architecture design pre-training and fine-tuning of vertical Large Language Models (LLMs) for the bio-genetics sector (e.g. gene interpretation breeding decision models) enhancing inference and generation capabilities in specific biological scenarios.

• Spearhead the cleaning standardization and feature engineering of multimodal biological data (genomics transcriptomics clinical phenotypes etc.) to construct high-quality instruction-tuning datasets and knowledge bases.
• Develop automated decision-making systems based on Multi-Agent frameworks achieving an end-to-end closed loop from natural language instructions to experimental protocol generation and equipment scheduling.
• Explore the application of cutting-edge AI technologies (such as Chain-of-Thought Reinforcement Learning and Knowledge Graphs) in precision medicine and smart breeding to address long-tail problems in traditional bioinformatics analysis.
• Collaborate closely with biologists and clinicians to translate complex biological problems into computable algorithmic models driving the deployment and iteration of algorithms in production environments.

Requirements

• Masters degree or higher in Computer Science Bioinformatics Artificial Intelligence or related fields with 3 years of algorithm development experience.
• Proficient in Python programming and deep learning frameworks like PyTorch or TensorFlow with a solid foundation in Transformer architecture and NLP algorithms.
• Hands-on experience in fine-tuning Large Language Models (LLMs); familiar with RLHF Prompt Engineering etc. Experience in developing models for the bio/medical vertical is highly preferred.
• Experience in Multi-Agent systems or Knowledge Graph development capable of handling complex logical reasoning and task planning.
• Familiar with basic bioinformatics workflows (e.g. GATK sequence alignment) and fundamental principles of genomics; possesses strong cross-disciplinary communication skills.

Preferred Qualifications

• Experience integrating with medical HIS/LIS systems or laboratory automation equipment is a plus.
• Publications in Nature/Sciencesub-journals or top-tier AI conferences in interdisciplinary fields are highly valued.
• Familiarity with cloud-native deployment and containerization technologies with experience in building large-scale data pipelines.

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