Faculty is the professional services arm of the Faculty. As a founding member of the Applied AI platform team, you will be responsible for leading the team building and maintaining the data science, ML ops, and deployment tooling that enables our team of over 100 Data Scientists and Engineers to deploy full-stack machine learning products for our customers.
What you’ll be doing:
You’ll be leading a small team, in collaboration with our customer-facing technologists. The platform you own will be a significant lever on the quality of our deployed software. Taking ownership of our existing tooling, you’ll identify and prioritize the technology our teams need to deliver our world-leading machine learning solutions, whether that’s new features for our notebook development environment, improvements to our model monitoring tooling, or how we deploy our systems into a variety of client environments.
What we’re looking for
- An engineering team leader who can take responsibility for the direction of a small team of engineers and the team’s roadmap.
- An experienced software engineer who loves building tools to enable others, understanding their impact, and improving them.
- Experience of the machine learning product lifecycle and how data scientists go from exploration to deployed models.
- Modern systems programming in at least one programming language e.g Scala, Python, Go
- Infrastructure-as-code and DevSecOps in one or more major cloud environments.
- Experience working as part of a small, fast-moving team.
- Distributed, containerized microservices architectures: docker, Kubernetes
Specifics that will help:
- MLOps using MLFlow, and Jupyter notebooks.
- Programming in Scala and Python: Some of our existing tooling is in Scala, and Python is the language of our data science workflows, but we’re open to using the right technologies for the job
- DevSecOps: Gitlab CI/CD, Helm
- IaaC: Cloud formation, Terraform
- Our systems run in AWS, but we’re looking at how to integrate with other cloud providers so experience in more than one will help.
- Experience in a platform/internal enablement team
Location: Hybrid – London
Type: Full time
Department: Engineering
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