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.
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Last updated on Oct 21, 2024