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Machine Learning Engineer | Cambridge

Job description

Breakthrough technology is vital for strengthening the UK’s Defence and Homeland Security. As an AI/ML Engineer Consultant, you will be at the forefront of this innovation race to defend and protect the UK from the latest technological and cyber threats.
Your work will have a real-world impact.

You will get to explore pioneering concepts by collaborating with elite multi-disciplinary teams of highly educated and skilled scientists, engineers, and designers. You’ll see ideas become a reality as you create prototypes through our rapid approach to design and implementation. It’s a fantastically challenging, varied, and agile role.

You will tackle diverse, real-world challenges from the ground up using your experience in designing and deploying systems that apply ML to a broad range of tasks, pulling together third-party components, as well as building elements yourself.
Our wide variety of intriguing projects, from proof-of-concept through to working prototypes, provide both intellectual and practical challenges giving opportunity to flex your problem-solving skills and creativity to devise innovative solutions.

The projects will test your broad exposure to the ML development cycle: data I/O, cleaning and preparation, rapid code prototyping, iterating model designs and deploying and packaging code into client-ready products.

You will have a track record of academic excellence, hold a relevant degree, and have proven technical capabilities. You will need a strong foundation in Python and current ML frameworks and notable experience in a number of the following areas:
  • Familiarity with popular ML libraries and frameworks like TensorFlow, PyTorch, Keras and scikit-learn.
  • Experience with neural network architectures, deep learning techniques, and building and training deep learning models.
  • Creating and handling large datasets including pre-processing steps and familiarity with data manipulation libraries like Pandas, NumPy, and data visualization tools such as Matplotlib or Seaborn.
  • Hands-on experience of building ML solutions for resource-constrained situations and deploying to edge-processing platforms.
  • Experience with emerging technologies such as GANs, LLMs, RL or XAI.