Senior Machine Learning Engineer
4 weeks ago
Faculty transforms organisational performance through safe, impactful and human-led AI.
We 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, as well as our award winning Fellowship.
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.
Our high-impact work has saved lives through forecasting NHS demand during covid, produced green energy by routing boats towards the wind, slashed marketing spend by predicting customer spending habits, and kept children safe online.
AI is an epoch-defining technology. We want people to join us who can help our customers reap its enormous benefits safely.
Working in our Defence business unit 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 space - examples of which can be found here
You are engineering-focused, with a keen interest and working knowledge of operationalised machine learning. To enable this, we work in cross-functional teams with representation from commercial, data science, product management and design specialities to cover all aspects of AI product delivery.
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;
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
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. Love finding new ways to solve old problems - when it comes to your work and professional development, you don't believe in 'good enough'. 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
Experience in Software Engineering including programming in Python.
Technical experience of cloud architecture, security, deployment, and open-source tools.
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