Machine Learning Engineer

About Faculty

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

With more than a decade of experience, we provide over 350 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 front lines of the world.

Because of the potential to work with our UK Defence clients, you will need to be eligible for UK SC clearance and willing to work up to three days per week on site with these customers, which may require travel to locations outside of our London base. The minimum requirement for SC clearance is 5 years continuous residence in the UK up to the present.

You will design, build, and deploy production-grade software, infrastructure, and MLOps systems that leverage machine learning. The work you do will help our customers solve a broad range of high-impact problems in the Defence and National Security arena.

You are engineering-focused, with a keen interest and working knowledge of ope rationalised machine learning. You have a desire to take cutting-edge ML applications into the real world. You will develop new methodologies and champion best practices for managing AI systems deployed at scale, with regard to technical, ethical and practical requirements. You will support both technical, and non-technical stakeholders, to deploy ML to solve real-world problems.

Our Machine Learning Engineers are 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 ope rationalise ML software.

As a rapidly growing organisation, 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.
• Working with senior engineers to scope projects and design systems
• Providing technical expertise to our customers
• Technical Delivery

You can view our company principles here. We look for individuals who share these principles and our excitement to help our customers reap the rewards of AI responsibly.

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 experience with the full machine learning lifecycle
• Working with Data Scientists to deploy trained machine learning models into production environments
• Working with a range of models developed using common frameworks such as Scikit-learn, Tensor Flow, or Py Torch
• Experience with software engineering best practices and developing applications in Python.
• Technical experience of cloud architecture, security, deployment, and open-source tools ideally with one of the 3 major cloud providers (AWS, GCP or Azure)
• Demonstrable experience with containers and specifically Docker and Kubernetes
• An understanding of the core concepts of probability and statistics and familiarity with common supervised and unsupervised learning techniques
• Demonstrable experience of managing/mentoring more junior members of the team
• Outstanding verbal and written communication.
• Excitement about working in a dynamic role with the autonomy and freedom you need to take ownership of problems and see them through to execution

We like people who combine expertise and ambition with…