About Faculty
Faculty transforms organisational performance through safe, impactful and human-led AI.
We are Europe’s leading applied AI company, founded in 2014, 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 has enabled us to partner with OpenAI, helping customers deploy cutting-edge generative AI safely.
Our high-impact work has saved lives, produced green energy, reduced marketing spend, and kept children safe online.
AI is an epoch-defining technology, and we seek individuals who can help our customers reap its enormous benefits safely.
What You'll Be Doing
You will design, build, and deploy production-grade software, infrastructure, and MLOps systems that leverage machine learning. Your work will help our customers solve high-impact problems in the Consumer and Services space.
You are engineering-focused, with a keen interest in operationalised machine learning. You will develop methodologies and champion best practices for managing AI systems deployed at scale, considering technical, ethical, and practical requirements. You will support both technical and non-technical stakeholders to deploy ML to solve real-world problems, working in cross-functional teams.
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 for 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 operationalising ML software.
Your key responsibilities will include:
- Working in cross-functional teams to deliver sophisticated, high-impact systems;
- Leading on the scope and design of projects;
- Offering leadership and management to junior engineers;
- Providing technical expertise to our customers;
- Ensuring Technical Delivery.
Who We're Looking For
At Faculty, your attitude and behaviour are just as important as your technical skill. We seek individuals who support our values, foster our culture, and deliver for our organisation. If you’re the right candidate, you probably:
- Think scientifically, testing assumptions and seeking evidence;
- Love finding new ways to solve problems and seek continuous improvement;
- Are pragmatic and outcome-focused, balancing the big picture with the details.
To succeed in this role, you’ll need the following illustrative requirements (70% is a rough guide):
- Understanding of the full machine learning lifecycle, including deploying models using frameworks like Scikit-learn, TensorFlow, or PyTorch;
- Understanding of probability and statistics and familiarity with supervised and unsupervised learning techniques;
- Experience in Software Engineering, particularly programming in Python;
- Technical experience in cloud architecture, security, deployment, and open-source tools, with hands-on experience in at least one major cloud platform;
- Experience with containers, specifically Docker and Kubernetes;
- Comfort in a high-growth startup environment;
- Outstanding verbal and written communication skills;
- Excitement about working in a dynamic role with autonomy to take ownership of problems.
What we can offer you:
The Faculty team is diverse and driven by intellectual curiosity. You’ll be surrounded by brilliant minds working towards collective goals, with opportunities to make your mark on a high-growth start-up poised for international expansion.
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