Lead Machine Learning Engineer

Job Description

About Faculty

At Faculty, we transform organisational performance through safe, impactful and human-centric AI.

With a decade of experience, we provide over 300 global customers with software, bespoke AI consultancy, and Fellows from our award winning Fellowship programme.

Our expert team brings together leaders from across government, academia and global tech giants to solve the biggest challenges in applied AI.

Should you join us, you’ll have the chance to work with, and learn from, some of the brilliant minds who are bringing Frontier AI to the frontlines of the world.

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 incl. National Security, Education, Public Services and the NHS.

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 - examples of which can be found here.

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; and

• Implementing and developing Faculty’s view on what it means to operationalise ML software.

We’re a rapidly growing organisation, so roles are dynamic and subject to change. Your role will evolve alongside business needs, but you can expect your key responsibilities to include:

• 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

Who We're Looking For

At Faculty, your attitude and behaviour are just as important as your technical skill. We look for individuals who can support our values, foster our culture, and deliver for our organisation.

To succeed in this role, you’ll need the following - these are illustrative requirements and we don’t expect all applicants to have experience in everything (70% is a rough guide):

• Understanding of and interest in the full machine learning lifecycle, including deploying trained machine learning models developed using common frameworks such as Scikit-learn, TensorFlow, or PyTorch

• Understanding of the core concepts of probability and statistics and familiarity with common supervised and unsupervised learning techniques

• An exposure to and eagerness for customer-facing work gauging the commercial value of projects and advising clients on technology strategy.

• Experience in Software Engineering including programming in Python.

• Proven experience with cloud architecture, security, deployment, and open-source tools on at least one major cloud platform, preferably AWS

• Demonstrable experience with containers and specifically Docker and Kubernetes

• Experience growing the technical capabilities of a team; adopting a caring attitude towards the personal and professional development of other engineers and an enthusiasm for nurturing a collaborative and accomplished engineering culture

We like people who combine expertise and ambition with optimism -- who are interested in changing the world for the better -- and have the drive and intelligence to make it happen. If you’re the right candidate for us, you probably:

• Think scientifically, even if you’re not a scientist - you test assumptions, seek evidence and are always looking for opportunities to improve the way we do things.

• Love finding new ways to solve old problems - when it comes to your work and professional development, you don’t believe in ‘good enough’. You always seek new ways to solve old challenges.

• Are pragmatic and outcome-focused - you know how to balance the big picture with the little details and know a great idea is useless if it can’t be executed in the real world.
  

What we can offer you:

The Faculty team is diverse and distinctive, and we all come from different personal, professional and organisational backgrounds. We all have one thing in common: we are driven by a deep intellectual curiosity that powers us forward each day.

Faculty is the professional challenge of a lifetime. You’ll be surrounded by an impressive group of brilliant minds working to achieve our collective goals.

Our consultants, product developers, business development specialists, operations professionals and more all bring something unique to Faculty, and you’ll learn something new from everyone you meet.