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Rplus Analytics

AI Engineer

Preston
Posted 1 day ago
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Company Description

Rplus Analytics is a technology consulting and analytics firm founded in 2012, specializing in AI-driven digital transformation for public sector and enterprise clients. The company partners with UK and Indian Government Departments to modernize data management and build cloud-native digital services, with a strong record of delivering scalable contracts. Rplus Analytics supports customers in migrating from on-premise to hybrid and cloud solutions, reducing technical debt and improving data quality to optimize costs and maximize data value. In addition to implementing commercial off-the-shelf solutions, the firm develops bespoke products such as DemandSense and PetaBolt, along with tailored large language models and private ChatGPT-style solutions for government departments. Based in the North of England and led by a female CEO, Rplus Analytics is committed to inclusive growth and actively supports diverse local talent in AI.

Role Description

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Strong

Only hits

No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.

This is a full-time remote role for an AI Engineer. The AI Engineer will design, build, and deploy AI and machine learning solutions that support digital transformation initiatives for public sector and enterprise clients. Day-to-day responsibilities include:

  • Developing and training models for pattern recognition, neural networks, and NLP tasks
  • Implementing scalable algorithms and APIs
  • Integrating AI components into cloud-native software systems

The role involves:

  • Collaborating with data scientists, software engineers, and client stakeholders to refine requirements, evaluate model performance, and ensure robust, maintainable production-grade solutions
  • Contributing to improving internal tools
  • Supporting bespoke products such as DemandSense and PetaBolt
  • Staying current with emerging AI techniques relevant to government and enterprise use cases

Qualifications

  • Strong foundation in Computer Science, including data structures, algorithms, and software engineering principles
  • Hands-on experience with Neural Networks and Pattern Recognition, including model training, evaluation, and optimization
  • Practical expertise in Natural Language Processing (NLP), such as text classification, information extraction, and language model integration
  • Proficiency in Software Development for AI systems using languages and frameworks such as Python, PyTorch, TensorFlow, or similar tools
  • Experience deploying AI solutions to cloud or hybrid environments (e.g., AWS, Azure, GCP) and working with CI/CD pipelines
  • Ability to work collaboratively in distributed teams, communicate technical concepts clearly, and engage with non-technical stakeholders
  • Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related quantitative field, or equivalent practical experience

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Beneficial:

  • Background in data engineering, model monitoring, or MLOps
  • Familiarity with public sector or regulated environments
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Skills

Neural Networks
Pattern Recognition
Natural Language Processing
Python
PyTorch
TensorFlow
Cloud Deployment
CI/CD
MLOps
Data Structures
Algorithms
Software Engineering
API Implementation
Model Optimization
Data Engineering

Location

Preston, England, United Kingdom

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