Local San Francisco Bay Area candidates only!
Hybrid contract - 3 days onsite and 2 days remote
Direct W2 contractors only! No 3rd party agencies!
Our client is looking for a Sr Data Scientist with experience in Machine Learning Engineering to join the Product Development Digital Strategy & Enablement team (PD-DSE). Clients 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.
As a Senior Data Scientist, you 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 PD organization to help our teams fulfill our mission: to do now what patients need next.
Key Accountabilities:
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, 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.
Qualifications:
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 cloud solutions (AWS / Azure / Google Cloud Platform), 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.
Experience with deployment of scalable apps a plus
Experience with clinical study data a plus
Education / Years of 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.
2+ years of commercial Data Engineering / ML Engineering / MLOps / UI/UX engineering experience
3+ years of commercial software engineering experience
TOP THREE MUST-HAVE QUALIFICATIONS:
- Recent LLM application development experience, in particular RAG applications.
- Strong general software development skills
- Good collaborator in a diverse team.
-Targeting level II ( 3-5 Years experience) senior level Data Scientist / ML engineer.