Dxc Technology
Bio-genetics
SeniorAIAlgorithmEngineer(Bio-genetics/SyntheticBiology)
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior AI Algorithm Engineer (Bio-genetics / Synthetic Biology) at Dxc Technology. Skills: Large Language Models, Bio-genetics, Algorithm development, Multi-Agent frameworks. Lead architecture design, pre-training, fine-tuning of LLMs. Enhance inference and generation capabilities”
What You'll Achieve.
Enhancing inference and generation capabilities; Achieving an end-to-end closed loop; Driving the deployment and iteration of algorithms in production environments
Industry & Context.
Address long-tail problems in traditional bioinformatics analysis; Translate complex biological problems into computable algorithmic models
What They're Looking For.
Must Have
Master’s degree or higher in Computer Science, Bioinformatics, Artificial Intelligence, or related fields, 3+ years of algorithm development experience, Proficient in Python programming, Deep learning frameworks like PyTorch or TensorFlow, Solid foundation in Transformer architecture, NLP algorithms, Hands-on experience in fine-tuning Large Language Models (LLMs), Familiar with RLHF, Prompt Engineering, Experience in Multi-Agent systems or Knowledge Graph development, Familiar with basic bioinformatics workflows, Possesses cross-disciplinary communication skills
Nice to Have
Experience in developing models for the bio/medical vertical, Experience integrating with medical HIS/LIS systems, Experience integrating with laboratory automation equipment, Publications in Nature / Science sub-journals or top-tier AI conferences in interdisciplinary fields, Familiarity with cloud-native deployment, Containerization technologies, Experience in building large-scale data pipelines
What You'll Do.
Lead architecture design
Enhance inference and generation capabilities
Spearhead data cleaning
Construct high-quality datasets and knowledge bases
Develop automated decision-making systems
Explore cutting-edge AI technologies
Collaborate with biologists and clinicians
Translate biological problems into algorithmic models
Drive deployment and iteration of algorithms
How You'll Work.
Team & Collaboration
Collaborate closely with biologists and clinicians; In-person collaboration
Communication Scope
Cross-disciplinary communication skills
Full Job Description
**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 stron
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