Founded In 2012, Callsign's mission has been to make Digital Identity simple and secure for everyone and everything. In that time, we've grown to over 200 employees, opened offices in Singapore and Abu Dhabi, been recognised as a WEF Global Innovator and our technology is being used by many of the world's leading financial institutions to keep millions of consumers safe.
We are looking for a new member to join our Machine Learning Engineering team. Currently we have a mature platform in Kubernetes but also expanding into a new serverless/streaming architecture. As part of the team you will help maintain these platforms but also contribute to architecting and deploying data quality monitors, observability and instrumentation for our models, feature stores and many more components critical to the data science lifecycle. You will also work closely with the Data Science team to help drive the development and deployment of models to production.
What the job involves:
- Architect and implement scalable and resilient AWS infrastructure solutions, adhering to industry best practices.
- Administer and scale service deployments in our Kubernetes clusters.
- Develop and automate deployment processes using infrastructure-as-code and CI/CD.
- Oversee the deployment and monitoring of machine learning models in production.
- Help setup our data warehousing solution and feature store.
- Collaborate with the data science team to streamline the release process, enable continuous integration, and facilitate seamless deployments.
- Collaborate with cross-functional teams to comprehend application requirements and provide infrastructure recommendations to optimise performance, security, and cost-efficiency.
- Strong software engineering skills in Python, including unit and integration testing.
- Knowledge of infrastructure as code, preferably terraform with AWS.
- Experience with Kubernetes cluster administration, deployment and scaling of services.
- Experience building CI/CD pipelines such as in Gitlab CI/CD.
- Experience with monitoring tools like prometheus and observability frameworks such as New Relic or Datadog.
- Experience in deploying and monitoring ML models.
- Desirable to have knowledge of ETL pipelines and data warehouses.
- Hybrid working, minimum 2 days on site
- Health Insurance, employee only
- Life Insurance
- Employee Assistance Program
- 3 months full pay maternity & 2 weeks full pay paternity
- 25 days of annual leave + Callsign Bank Holiday + flexibility of 2 weeks remote working
- Free financial advice
Optional:
- Cycle to work scheme
- Wills and Estates – our benefits provider has partnered with a third party who offers a discount
- Home Utilities our benefits provider has partnered with a third party who offers a discount
- Cycle Insurance
- Health cash plans
- Cyclist protection
- Discounted gym membership