Faculty transforms organisational performance through safe, impactful and human-led AI.
We are Europe's leading applied AI company, founded in 2014 with our Fellowship programme, training academics to become commercial data scientists. Today, 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 across UK Defence, Government, Life Sciences, Energy, Banking, and Retail. As a Machine Learning Engineer, you will work in the business area where the need is greatest, which may change depending on our external client requirements. You will need to be eligible for 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.
What You'll Be Doing:
You will design, build, and deploy production-grade software, infrastructure, and MLOps systems that leverage machine learning. You are engineering-focused, with a keen interest and working knowledge of operationalised machine learning. You will develop new methodologies and champion best practices for managing AI systems deployed at scale, supporting both technical and non-technical stakeholders.
Your key responsibilities will include:
- Building software and infrastructure that leverages Machine Learning;
- Creating reusable, scalable tools to enable better delivery of ML systems;
- Working with our customers to understand their needs;
- Collaborating 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.
As a rapidly growing organisation, roles are dynamic and subject to change. 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.
Who We're Looking For:
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;
- Experience with common frameworks such as Scikit-learn, TensorFlow, or PyTorch;
- 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, specifically Docker and Kubernetes;
- An understanding of 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 to take ownership of problems and see them through to execution.