They are a team on a mission, to put accessible and affordable healthcare in the hands of every person on earth. Their mission is bold and ambitious, and it’s one that’s shared by their team who shares their values, to dream big, build fast and be brilliant.
To achieve this, they’ve brought together one of the largest teams of scientists, clinicians, mathematicians, and engineers to focus on combining the ever-growing computing power of machines, with the best medical expertise of humans, to create a comprehensive, immediate, and personalized health service and make it universally available.
At Babylon their people aren’t just part of a team, they’re part of something bigger. They’re a vibrant community of creative thinkers and doers, forging the way for a new generation of healthcare. They’re only as good as their people. So, finding the best people is everything to them.
They serve millions, but they choose their people one at a time…
Purpose of Role
Their applied AI team is looking for a skilled and experienced data science engineer with being hands-on in the development of AI models. The role will initially be focused on creating and scaling data pipelines and model deployment infrastructure for their healthcare AI products deployed globally. These products touch and improve the lives of millions on a daily basis and contribute to their mission of making affordable healthcare and accessible for everyone.
The role is embedded in the product engineering organization and will work alongside data scientists, software engineers, and other product and design teams. For the right candidate, it will be a great opportunity to be involved in end to end product development life cycles- from ideas through discovery, to launch and expansion of new products/features.
Key Responsibilities:
To work alongside a team of researchers, data scientists, and software engineers to help build and improve models. Creating the tooling to ease deployment of models, and monitoring accuracy needed for new model development and experimentation.
Key Skills required:
– Strong software engineering skills in Python and SQL.
– Familiarity with Numpy, Flask, SQLAlchemy and other similar python toolkits will be beneficial
– Ability to code and manage generic inference API’s
– In-depth understanding of PGM, Bayesian Networks, knowledge graphs
– Knowledge of professional software engineering best practices for the full software development life cycle, strong OO design skills)
Person Specification
This is a senior role and involves stakeholders and possibly line management. The ideal candidate will have great communication skills (both written and spoken) to engage with different stakeholders and highlight the value/risks of various workstreams.
– Comfortable with ambiguity and able to handle frequent changes, customary to a rapidly growing organization.
– Work in a team or as a lone contributor to start and shape new ideas.
Qualifications and Experience:
Essential:
– Hands-on experience with model building for ML and non-traditional ML applications.
– Working around cold-start issues and transitioning to production data.
– Well versed in Python, SQL, and python tool kits. Experience in developing, delivering, and managing production software.
– Good coding skills to differentiate between exploratory notebook code and deployment version.
– Designing and updating inference APIs and latency monitoring.
– Knowledge of data optimization techniques and integrity verification.
Desirable:
– Familiarity with Kubernetes and kubeflow
– Experience of AI and ML model building and best practices.
– Experience of using off-the-shelf AI/ML platforms and data products such as Databricks/Spark, AWS Sagemaker , Kafka.
– Experience with designing infrastructure around data platforms, preferably with serverless deployment configuration.
