About Relation
We are an end-to-end biotech developing transformational medicines, with technology at our core. Our ambition is to understand human biology in an unprecedented way; discovering therapies that will treat some of life's most devastating diseases. We leverage single-cell multi-omics directly from patient tissue, functional assays and machine learning to drive disease understanding, from cause to cure.
We are committed to building diverse and inclusive teams. We are an equal opportunities employer and do not discriminate on the grounds of gender, sexual orientation, marital or civil partner status, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability or age. We strive to create an interdisciplinary workplace that cultivates innovation through collaboration, and we empower each of our team members to do their best work and develop to their highest potential.
By joining Relation, you will be part of an exceptionally talented team, you’ll have extraordinary leverage to push the field of drug discovery, and you’ll help us shape our culture and strategic direction. Ultimately, your impact will be felt in patients’ lives.
The opportunity
As a Software Engineer in our Platform Team, you will join the engineering team in a role pivotal to our mission to revolutionize target discovery and validation using advanced machine learning models. You will work closely with the Machine Learning and Data Science teams, designing and scaling our hybrid compute cluster, building core-platform services, ensuring optimal performance, reliability, and scalability.
Role responsibilities
Develop, evolve, and contribute to the architectural strategy for our Kubernetes-based clusters spread across our private cloud and multiple public clouds.
Engineer and manage the full-lifecycle of internal and public-facing applications, APIs, and services.
Enhance continuous integration and continuous delivery pipelines, facilitating efficient development, testing, and deployment processes
Establish comprehensive monitoring solutions to proactively detect and resolve issues.
Ensure robust backup, disaster recovery, and failover strategies are in place.
Enforce best practices and security measures to protect sensitive data and comply with industry standards.
Work closely with Machine Learning and Data Science teams to understand their computational needs and challenges. Provide expert guidance and support to ensure their success
Professionally, you have
A Bachelor’s in Computer Science or a related quantitative field. A minimum of 3 years of combined experience in software engineering, with a demonstrated ability to design, deploy, and manage cloud infrastructure and Kubernetes clusters. Bonus: experience developing and deploying applications on Kubernetes.
Solid experience in setting up and maintaining CI/CD pipelines using tools like GitHub Actions and ArgoCD. Experience with infrastructure as code (IaC) tools such as Terraform.
Solid Python coding experience, with the ability to write clean, efficient, and maintainable code. Bonus: experience with Go.
Excellent analytical and troubleshooting skills, with a systematic approach to solving complex problems.
Strong verbal and written communication skills, with the ability to effectively collaborate with cross-functional teams.
Bonus: experience with DataOps and MLOPs
Personally, you are
Join us in this exciting role where your contributions will have a direct impact on advancing our understanding of genetics and disease risk, supporting our mission to get transformative medicines to patients. Together, we're not just doing research; we're setting new standards in the field of machine learning and genetics. The patient is waiting!
Relation Therapeutics is a committed equal opportunities employer.
RECRUITMENT AGENCIES: Please note that Relation Therapeutics does not accept unsolicited resumes from agencies. Resumes should not be forwarded to our job aliases or employees. Relation Therapeutics will not be liable for any fees associated with unsolicited CVs.
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