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
- Master’s 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/Science sub-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.
At DXC Technology, we believe strong connections and community are key to our success. Our work model prioritizes in-person collaboration while offering flexibility to support wellbeing, productivity, individual work styles, and life circumstances. We’re committed to fostering an inclusive environment where everyone can thrive.
Recruitment fraud is a scheme in which fictitious job opportunities are offered to job seekers typically through online services, such as false websites, or through unsolicited emails claiming to be from the company. These emails may request recipients to provide personal information or to make payments as part of their illegitimate recruiting process. DXC does not make offers of employment via social media networks and DXC never asks for any money or payments from applicants at any point in the recruitment process, nor ask a job seeker to purchase IT or other equipment on our behalf. More information on employment scams is available here.
