Data Scientist - Machine Learning

Data Scientist - Machine Learning ROCGJP00027870 A leading biotechnology company is seeking a Data Scientist - Machine Learning. The right candidate will work closely with multi-disciplinary teams to design, develop and deploy structured, high-quality data solutions in particular Large Language Model (LLM) applications. These solutions will be leveraged across the Product Development organization to help our teams fulfill our mission: to do now what patients need next. We focus on delivering technology that evolves the practice of medicine and helps patients live longer, better lives. We are a diverse team of open and friendly people, enthusiastic about technological novelties and optimal enterprise solutions. We share knowledge, experience & appreciate different points of view. Data Scientist - Machine Learning Pay and Benefits: * Hourly pay: $75-$85/hr (pay varies based on candidate's experience) * Worksite: Leading biotechnology company (South San Francisco, CA 94080) * W2 Employment, Group Medical, Dental, Vision, Life, Retirement Savings Program, PSL * 40 hours/week, 12 Month Assignment Data Scientist - Machine Learning Responsibilities: * Partner with fellow Data Scientists, ML engineers, MLOps / DevOps engineers and cross functional teams to solve complex problems and create unique solutions by using modern NLP technologies in particular LLMs. * Build data pipelines and deployment pipelines for ML models. * Development of ML models according to business and functional requirements. * Able to help deploy various models and tune them for better performance. * Document and communicate the design and implementation details. * Contribute to the DSE AI team on technical decisions. * Collaborate with clients, and informatics departments to deploy scalable and easy-to-maintain solutions. * Serves as a technical point of contact for enterprise-wide technologies solutions. Leads complex troubleshooting efforts and root cause analysis. Data Scientist - Machine Learning Qualifications: * 2+ years of commercial Data Engineering / ML Engineering / MLOps / UI/UX engineering experience. * 3+ years of commercial software engineering experience. * Master in quantitative field (e.g. mathematics, statistics, computer science, EE, etc.), and/or Life Sciences degree with significant computational experience, or equivalent, with 5+ year working experience in Data Science. PhD a plus. * Experience with LLM applications development including tool using and reasoning, for instance RAG solution and code interpreter. * Experience with LLM fine tuning a big plus. * Experience in building data pipelines and deployment pipelines for LLM applications * Recent experience with ML/AI toolkits such as AWS Sagemager (other toolkits like Pytorch, Tensorflow, Keras, MXNet, H20, etc are nice to have). * Experience with MLOps technologies (Sagemaker, Vertex AI, Kubeflow). * Experience with deployment of scalable apps a plus. Experience with clinical study data a plus. * Experience with cloud solutions (AWS / Azure / GCP), docker. * Proven scripting and automation skills. * Good knowledge of: git, bash, linux, CI/CD tools (e.g. jenkins, gitlab CI), software lifecycle, RDB, visualization tools eg Tableau, Jira, confluence. * Programming languages: Python, R. * Test driven development, good coding practices. * Problem-solving and decision-making skills. * Good interpersonal skills. * Customer & delivery focus. * Ability to work effectively with team members and virtual teams from different locations and different cultural backgrounds.