About the position
As a Data Engineer at Mednet, you will play a pivotal role in scaling our operations to new medical fields and enhancing our underlying knowledge platform. This position is crucial as we aim to support new insights and products that will further our mission of improving patient outcomes through better medical decision-making. You will be the first data engineering hire, which means you will have the unique opportunity to shape the data engineering practices and processes within the company. Working closely with our CTO and engineering team, you will be responsible for ingesting and structuring medical data, designing a robust data pipeline, and creating services that will allow us to efficiently scale our offerings to doctors in various specialties. Your work will directly impact our editorial operations and the evolution of our data products. You will leverage large language models (LLMs) and contribute to the design of the Mednet knowledge graph, which is essential for organizing and retrieving medical information effectively. This role requires a strong passion for social impact, as the work you do will help doctors make informed decisions that can significantly affect patient care. You will be expected to take ownership of mission-critical services, ensuring they are reliable and scalable as we grow. Your contributions will be vital in helping us maintain our position as the leading digital platform for oncologists and expand our reach into other medical fields.
Responsibilities
- Ingest and structure medical data for various specialties.
- Design and implement a scalable data pipeline and services.
- Collaborate with the CTO and engineering team to enhance data processing capabilities.
- Utilize large language models (LLMs) to improve data products and editorial operations.
- Contribute to the design and development of the Mednet knowledge graph.
Requirements
- 4-10 years of engineering experience.
- Experience with designing and building production systems.
- Ability to own standalone mission-critical services.
- Passion for work that has a social impact.
Nice-to-haves
- Experience working with LLMs (open and closed source) and/or NLP.
- Experience with Spark.
- Experience with Go.
- Experience building recommendation systems.
- Experience working with medical claims data.
- Understanding of medical terminology and the healthcare system.
- Experience or familiarity with The Medical Subject Headings (MeSH).
- Familiarity with the Python scientific computing stack (Pandas, Numpy, SKLearn, etc.).
