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Machine Learning Engineer, AI

Summary

Research and prototype AI models (generative, adversarial) for UK government projects, using Python, PyTorch, and Docker to build proofs of concept.

  • Work on exciting public sector projects and make a positive difference in people’s lives.
  • Research machine learning models and evaluate their application within the specialist domain.
  • Collaborate with a small team to deliver AI capabilities for the UK government.
  • Keep learning about various AI techniques such as classical ML, generative, and adversarial methods.
  • Experiment with new approaches and translate them into practical capabilities.

Requirements

  • Model Research & Evaluation: Research emerging machine learning models and techniques, and assess how they could be applied within our specialist domain.
  • Applied AI Research: Turn research into practical proofs of concept, exploring generative, adversarial and other AI approaches.
  • Domain Application: Work with the team to understand our customers problems in depth and translate ML capability into solutions that fit their specialist domain.
  • Continuous Learning: Keep pace with the fast moving field of AI building knowledge across different model types and techniques and sharing what you learn with the team.
  • Research Skills: Comfortable reading and evaluating ML research and translating findings into practical ideas worth testing.
  • Technology Implementation: Ability to evaluate new AI technologies generative, adversarial or otherwise for relevance and feasibility within the UK Government Domain.
  • Advanced Prototyping: Ability to build proof of concept applications that bridge the gap between initial research and real-world application.
  • Specialist Advice: Keen to grow into a technical resource for the practical application of AI within the organisation, sharing knowledge as your expertise builds.
  • Data Science: Applying data science techniques to support model research, evaluation, and refinement.
  • Team Fit: A quick learner who's easy to work with, and will slot naturally into a close-knit, high-performing team.
  • Technical Expertise: Solid understanding of machine learning algorithms and frameworks with a general grounding in software engineering practices and a genuine curiosity about how ML models work.
  • Python: Strong proficiency and hands-on programming experience in Python are required.
  • ML Frameworks: Practical experience working with machine learning frameworks (e.g. Pytorch) to build, train, evaluate, and deploy models.
  • Version Control: Proficiency with Git for version control and collaborative development is required.
  • Containerisation: Familiarity with Docker is required to package, deploy, and run applications across environments.
  • Frontend Development: Experience with frontend technologies, specifically JavaScript and React, to help build interactive user interfaces for our prototypes (nice to have).
  • Cloud Services: Experience working with cloud platforms (e.g., AWS, Azure, GCP) (nice to have).
  • Systems/Backend Languages: Familiarity with other languages used for high-performance backend or ML workloads, such as Rust or C++ (nice to have).

Core Competencies

Demonstrates expertise in machine learning model research and evaluation, with a strong proficiency in Python and experience in applying AI techniques within the public sector. Capable of building proof of concept applications and collaborating effectively within a high-performing team.

Highest-signal resume keywords

  • Machine Learning Research
  • Python Programming
  • ML Frameworks (Pytorch)
  • Data Science Techniques
  • Version Control (Git)

ATS Optimization Keywords

Hard Skills

  • Machine Learning Algorithms
  • Generative AI Techniques
  • Adversarial AI Techniques
  • Advanced Prototyping
  • Data Science
  • Model Evaluation
  • AI Technology Evaluation
  • Software Engineering Practices
  • Cloud Platforms (AWS, Azure, GCP)
  • Systems/Backend Languages (Rust, C++)

Soft Skills

  • Continuous Learning
  • Team Collaboration
  • Adaptability
  • Problem-Solving
  • Communication

Industry Keywords

  • Public Sector Projects
  • AI Capabilities
  • Proofs of Concept
  • Specialist Domain
  • Machine Learning Techniques

Tools & Technologies

  • Pytorch
  • Docker
  • Git
  • JavaScript
  • React

See also

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