Causalis is a VC-backed startup partnering with the world’s leading pharma companies, building
machine learning solutions to bring causal intelligence to healthcare. We are developing a platform of
solutions based on novel and proprietary causal AI techniques, to help doctors, patients, and
researchers understand and act on the cause-effect relationships in medical data. We are a
multi-disciplinary, international team of experts in AI and ML, causal inference and data science,
healthcare and medicine. We are looking for smart, driven and overall extraordinary individuals who
are passionate about changing the world of personalized medicine, and eager to shape the future of
Please contact us with CV/resume at
Infrastructure Development
We're looking for an experienced engineer to work closely with the CTO on data and ML infrastructure.
You will help define strategy and execution for our backend (including devops, security and compliance,
data ingestion and databases), and ensure that we provide reliable and scalable service internally and
How you’ll contribute:
Architect and develop health data processing systems for ingestion, integration, storage, and
consumption for internal and external users (and at multiple scales)
Lead the design and development of infrastructure to support MVP and multiple phases of
Design ETL data models that allow easy storage and retrieval of complex data types
Develop logging, metrics, and alerts that enable us to ensure the data pipelines are up to date
and functioning
Collaborate with internal and external software engineers to develop data models and schemas
that help provide easy access to complex data sets
Work with data scientists and ML engineers to help build efficient workflows for experimenting
with many varied datasets
Our ideal candidate will bring:
Experience with secure data pipelines
4+ years of industry experience working with backend systems and platforms
Experience developing CI/CD pipelines, and MLOps infrastructure
Experience writing production-level code in Python
Significant experience as an AWS certified architect
Experience with SQL databases and queries, and designing data schemas
Ability to lead complex software engineering projects from design to completion
Excellent communication skills and ability to work with technical and non-technical partners
from many teams
Nice to have:
Strong experience with health/medical data pipelines (including protocols HIPAA, FHIR, etc.)
Experience in the early-stage startup environment
Acted as a technical lead for small engineering teams
Working knowledge of data science
Fullstack and/or front-end experience