Description
Faculty is looking for a Lead Machine Learning Engineer to spearhead the technical direction and delivery of complex AI and software projects. As a Lead Machine Learning Engineer, you will act as a technical expert, applying your skills across various projects from solution architecture to client-side deployments, while ensuring engineering decisions are sound and reliable.
The role demands a balance of deep technical expertise and strong leadership, focusing on driving innovation, fostering team growth, and building reusable solutions across the organisation. You will set the technical direction for complex ML and software projects, balance trade-offs, and guide team priorities. You will also architect, implement, and maintain reliable, scalable ML/software systems, and justify key architectural decisions.
Responsibilities:
- Setting the technical direction for complex ML and software projects
- Architecting, implementing, and maintaining reliable, scalable ML/software systems
- Defining project problems, developing roadmaps, and overseeing delivery across multiple workstreams
- Driving the development of shared resources and libraries across the organisation
- Leading hiring processes, making informed selection decisions, and mentoring multiple individuals
- Proactively developing and executing recommendations for adopting new technologies, tools, and changing our ways of working
- Acting as a technical expert and coach for customers
Requirements:
- Technical expert among peers, capable of going deep on particular topics and demonstrating breadth of knowledge
- Strong software engineering skills in Python and at least one compiled or strongly-typed language
- Expert in at least one major Cloud Solution Provider (e.g., Azure, GCP, AWS)
- Hands-on experience with containerisation tools like Docker and orchestration via Kubernetes
- Experience managing and coaching a team of engineers
- Excellent communicator who can proactively help customers achieve their goals
Our interview process consists of five stages: Talent Team Screen, Introduction to the role, Pair Programming Interview, System Design Interview, and Commercial & Leadership Interview.
We encourage applications from people of all backgrounds, ethnicities, genders, religions, and sexual orientations.