Lead Machine Learning Engineer
3 weeks ago
Faculty is a leading applied AI company that transforms organisational performance through safe, impactful and human-led AI. With a decade of experience in AI, we provide over 300 global customers with industry-leading software and bespoke AI consultancy for retail, healthcare, energy, and governmental organisations. Our expertise and safety credentials are such that OpenAI asked us to be their first technical partner, helping customers deploy cutting-edge generative AI safely.
About the Role:
This role is situated within our Applied AI consultancy, serving clients in our Government & Public Services business unit working on projects across a wide range of areas. As a Lead Machine Learning Engineer, you'll split your time between designing, building, and deploying production-grade software, infrastructure, and MLOps systems and offering leadership and mentorship to more junior engineers on the team. Because of the potential to work with our National Security and Policing clients, you will need to be eligible for Security Clearance and you may also be required to travel to locations outside of our London office.
What You'll Be Doing
Working in our Government and Public Services business unit you will be helping our customers solve a broad range of high-impact problems in the Government and Public services space. You are engineering-focused, with a working knowledge of or keen interest in taking cutting-edge ML applications into the real world. You'll develop new methods and champion best practices for managing AI systems deployed at scale and collaborate with both technical and non-technical stakeholders to deploy ML to solve real-world problems.
The Machine Learning Engineering team is responsible for the engineering aspects of our customer delivery projects. As a Machine Learning Engineer, you'll be essential to helping us achieve that goal by:
- Building software and infrastructure that leverages Machine Learning
- Creating reusable, scalable tools to enable better delivery of ML systems
- Working with our customers to help understand their needs
- Working with data scientists and engineers to develop best practices and new technologies
- Implementing and developing Faculty's view on what it means to operationalise ML software.
- Working in cross-functional teams of engineers, data scientists, designers and managers to deliver technically sophisticated, high-impact systems.
- Leading on the scope and design of projects
- Offering leadership and management to more junior engineers on the team
- Providing technical expertise to our customers
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