Machine Learning Engineer, AI

Jobtailor

Cheltenham

On-site

GBP 55,000 - 75,000

Full time

14 days+

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Job summary

Jobtailor is seeking a hands-on AI researcher to work on UK public sector projects, researching ML models and evaluating their application within our specialist domain. You will collaborate with a small team to deliver AI capabilities for the UK government and translate research into practical proofs of concept.

You will continually learn about ML techniques from classical to generative and adversarial methods, building prototype solutions that bridge research and real-world applications.

Qualifications

Research emerging machine learning models and techniques, and assess how they could be applied within our specialist domain.
Turn research into practical proofs of concept, exploring generative, adversarial and other AI approaches.
Work with the team to understand our customers problems in depth and translate ML capability into solutions that fit their specialist domain.
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.
Comfortable reading and evaluating ML research and translating findings into practical ideas worth testing.
Ability to evaluate new AI technologies generative, adversarial or otherwise for relevance and feasibility within the UK Government Domain.
Ability to build proof of concept applications that bridge the gap between initial research and real-world application.
Keen to grow into a technical resource for the practical application of AI within the organisation, sharing knowledge as your expertise builds.
Applying data science techniques to support model research, evaluation, and refinement.
A quick learner who's easy to work with, and will slot naturally into a close-knit, high-performing team.
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.
Strong proficiency and hands-on programming experience in Python are required.
Practical experience working with machine learning frameworks (e.g. Pytorch) to build, train, evaluate, and deploy models.
Proficiency with Git for version control and collaborative development is required.
Familiarity with Docker is required to package, deploy, and run applications across environments.
Experience with frontend technologies, specifically JavaScript and React, to help build interactive user interfaces for our prototypes (nice to have).
Experience working with cloud platforms (e.g., AWS, Azure, GCP) (nice to have).
Familiarity with other languages used for high-performance backend or ML workloads, such as Rust or C++ (nice to have).

Responsibilities

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).

Skills

Python Programming

ML Frameworks (Pytorch)

Data Science Techniques

Git Version Control

Generative AI Techniques

Adversarial AI Techniques

Advanced Prototyping

Cloud Platforms (AWS, Azure, GCP)

Rust / C++

Docker

JavaScript

React

Tools

Docker

Git

JavaScript

React

AWS

Azure

GCP

Rust

C++

Job description

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.

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