Rplus Analytics
AI Engineer
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Company Description
Rplus Analytics is a technology consulting and analytics firm founded in 2012, specializing in digital transformation for UK Government Departments and global public and private sector enterprises. The company focuses on modernizing data management through AI, deep tech, and cloud-native digital services, including efficient migration from on-premise to hybrid and cloud solutions. Rplus Analytics develops both CoTS-based and bespoke products, with flagship data science solutions such as DemandSense and PetaBolt. The organization builds tailored Large Language Models and private conversational AI solutions to help government departments maximize data exploitation and efficiency, and is exploring Artificial General Intelligence to address public sector challenges. Based in the North of England, Rplus Analytics is committed to inclusive growth and developing local talent, fostering a welcoming environment for all professionals in AI.
Role Description
This is a full-time remote role for an AI Engineer at Rplus Analytics. The AI Engineer will design, develop, and deploy AI models and solutions, including pattern recognition systems, neural network architectures, and NLP-based applications for public sector and enterprise clients. Day-to-day responsibilities include collaborating with cross-functional teams to understand requirements, implementing scalable software components, integrating AI services into cloud-native environments, and optimizing performance and reliability. The role involves working on data preprocessing and feature engineering, evaluating model accuracy and robustness, documenting technical designs, and contributing to the continuous improvement of in-house data science products and reusable AI components. The AI Engineer will also support experimentation with emerging AI techniques and tools, aligning solutions with security, compliance, and cost-efficiency goals.
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Qualifications
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- Strong foundation in Computer Science and Software Development, including algorithms, data structures, and coding in languages such as Python, Java, or similar.
- Proficiency in Neural Networks and Pattern Recognition, with experience building, training, and deploying models using modern machine learning frameworks.
- Hands-on experience with Natural Language Processing (NLP), including working with Large Language Models and text analytics for practical applications.
- Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization or orchestration tools for deploying AI solutions at scale.
- Familiarity with data engineering practices, including data pipelines, ETL processes, and working with structured and unstructured datasets.
- Ability to write clean, maintainable code, follow software development best practices, and use version control and CI/CD tools.
- Strong analytical and problem-solving skills, with the ability to translate complex requirements into robust technical solutions.
- Bachelor’s or master’s degree in Computer Science, Engineering, Mathematics, Data Science, or a related field, or equivalent practical experience.
- Experience working on public sector, enterprise, or large-scale analytics projects is an advantage.
- Commitment to collaborative
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