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Machine Learning Engineer, Senior

2 months ago

Bournemouth, Bournemouth, United Kingdom Faculty Full time
About Faculty

We're a leading applied AI company, transforming organisational performance through safe, impactful and human-led AI.

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.

We provide over 300 global customers with industry-leading software, and bespoke AI consultancy for retail, healthcare, energy, and governmental organisations.

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.

We're looking for talented Machine Learning Engineers to join our Defence business unit, working on high-impact projects that leverage machine learning to solve real-world problems.

Key Responsibilities
  • Design, build, and deploy production-grade software, infrastructure, and MLOps systems that leverage machine learning.
  • Develop new methodologies and champion best practices for managing AI systems deployed at scale, with regard to technical, ethical and practical requirements.
  • Support both technical and non-technical stakeholders to deploy ML to solve real-world problems.
  • Work in cross-functional teams with representation from commercial, data science, product management and design specialities to cover all aspects of AI product delivery.
Requirements
  • 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.
  • Experience in Software Engineering including programming in Python.
  • Technical experience of cloud architecture, security, deployment, and open-source tools.
What We Offer

We operate a hybrid way of working, meaning that you'll split your time across client location, Faculty's Old Street office and working from home depending on the needs of the project.

We're looking for talented individuals who combine expertise and ambition with optimism, and have the drive and intelligence to make a real impact.

We offer a dynamic and supportive work environment, with opportunities for professional development and growth.