Responsibilities
- Create and implement AI and machine learning models for predictive, prescriptive, and generative insights in healthcare contexts.
- Develop systems using large language models, retrieval-augmented generation, and agent-based architectures.
- Construct and refine full-cycle data and model pipelines using Python, PySpark, SQL, and related tools.
- Fine-tune and maintain generative AI models for natural language processing, summarization, and interactive AI applications.
- Apply MLOps standards including model tracking, performance monitoring, optimization, and automated deployment workflows.
- Utilize cloud infrastructure such as Azure, AWS, and GCP for scalable model hosting and data processing.
- Work with data warehouse platforms like Snowflake and build robust, high-volume data workflows.
- Operate within Agile teams, contributing to planning cycles and using Git-based repositories for version control.
- Maintain strict adherence to data privacy and regulatory requirements for sensitive health information.
- Support growth and development of less experienced team members through guidance and knowledge sharing.
- Build and launch intelligent systems that solve complex business problems with ethical AI principles.
Work Arrangement
Hybrid
Other
- All remote workers must comply with the company's telecommuting policy.
- The position will remain open for at least two business days or until a suitable number of applicants is received; the posting may close early due to high application volume.
- Employment is contingent upon passing a drug screening.
- In accordance with the San Francisco Fair Chance Ordinance, individuals with arrest or conviction records may still be considered for employment.
- The company complies with Equal Employment Opportunity regulations and does not discriminate based on race, religion, age, sex, national origin, sexual orientation, gender identity, disability, veteran status, or other protected characteristics under applicable laws.
