Data Scientist - Machine Learning Engineer

Csi - South San Francisco, CA

Full-time - Mid Level

South San Francisco, CA

Professional, Scientific, and Technical Services

About the position

The Sr Data Scientist / Machine Learning Engineer will join the Product Development Digital Strategy & Enablement team, focusing on delivering innovative technology solutions that enhance medical practices and improve patient outcomes. This role involves collaborating with cross-functional teams to design, develop, and deploy high-quality data solutions, particularly in the realm of Large Language Model (LLM) applications. The ideal candidate will possess strong software development skills and recent experience in LLM application development, specifically with RAG applications.

Responsibilities

• Partner with fellow Data Scientists, ML engineers, MLOps / DevOps engineers and cross-functional teams to solve complex problems using modern NLP technologies, particularly LLMs.
• Build data pipelines and deployment pipelines for ML models.
• Develop ML models according to business and functional requirements.
• Deploy various models and tune them for better performance.
• Document and communicate 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.
• Serve as a technical point of contact for enterprise-wide technology solutions, leading troubleshooting efforts and root cause analysis.

Requirements

• Experience with LLM applications development, particularly RAG solutions and code interpreters.
• Experience in building data pipelines and deployment pipelines for LLM applications.
• Recent experience with ML/AI toolkits such as AWS Sagemaker, with knowledge of other toolkits like Pytorch, Tensorflow, Keras, MXNet, H20 being a plus.
• Experience with MLOps technologies (Sagemaker, Vertex AI, Kubeflow).
• Experience with cloud solutions (AWS / Azure / Google Cloud Platform) and Docker.
• Proven scripting and automation skills.
• Good knowledge of git, bash, Linux, CI/CD tools (e.g., Jenkins, GitLab CI), software lifecycle, RDB, and visualization tools (e.g., Tableau, Jira, Confluence).
• Proficiency in programming languages such as Python and R.
• Test-driven development and good coding practices.
• Strong problem-solving and decision-making skills.
• Good interpersonal skills and customer delivery focus.

Nice-to-haves

• Experience with deployment of scalable applications.
• Experience with clinical study data.