ENVIRONMENT:

A fast-growing UK-based SaaS company seeks a highly experience Machine Learning & AI Engineer to join its team. In this role, you'll work on impactful projects leveraging advanced AI, Machine Learning, and Data Science techniques to support autonomous data-driven decision-making processes and deliver personalised customer experiences across its platform. You will design, develop, and deploy a range of AI and ML products and features, using LLMs and other analytical and predictive AI solutions. The ideal candidate will require a Bachelor's Degree in a Science or Engineering discipline, have a minimum of 2 years of experience in Machine Learning and generative AI feature development, with expertise in NLP and experience developing and deploying NLP models for text and token classification, sentence similarity, anomaly detection, and text generation. You will also need an understanding of transformer-based architecture and experience with the HuggingFace ecosystem and AI/ML frameworks (e.g., TensorFlow, PyTorch).

DUTIES:

Machine Learning Development -

• Design, develop, and deploy ML models and algorithms to solve complex business problems.
• Develop and enhance NLP models for classification, insights extraction, task prioritisation, and recommendation systems.
• Work with structured and unstructured data to analyse trends and develop solutions that improve decision-making and automation.
• Ensure that all AI models and data handling practices comply with relevant laws and ethical guidelines.

Prompt Engineering & Generative AI -

• Develop and expand the capabilities of its LLMs and interactive AI assistant, focusing on generative AI applications.
• Refine and optimise LLM output and reliability using prompt engineering techniques.
• Incorporate techniques like Retrieval-Augmented Generation (RAG), vector databases, and semantic searches to improve precision and relevance in data extraction from large datasets.
• Collaborate with product and stakeholders to define AI use cases and implement effective prompting strategies.

MLOps & AI Infrastructure -

• Architect and maintain scalable, containerised environments for AI model deployment.
• Implement and manage CI/CD pipelines for seamless integration and delivery.
• Integrate the experiment tracking and monitoring tools to record modelling progress and deployment performance.
• Leverage model optimisation and quantisation frameworks to streamline model inference, reduce latency, and enable efficient scaling of ML deployments.

Collaboration & Innovation -

• Must be able to work closely with Data Scientists, Software Engineers, and Product teams to define requirements and deliver AI-driven solutions.
• Continuously monitor advancements in AI and LLM technologies and review relevant academic literature and industry releases to ensure our strategies and implementations align with the latest innovations and standards.
• Prototype ML systems and AI concepts, particularly those using NLP and LLMs, and evaluate the effects of different models and techniques on AI performance.

REQUIREMENTS:

Qualifications -

• Bachelor's Degree in a Science or Engineering discipline.

Experience/Skills -

• At least 2 years of experience in Machine Learning and generative AI feature development, with expertise in NLP.
• Experience developing and deploying NLP models for text and token classification, sentence similarity, anomaly detection, and text generation.
• An understanding of transformer-based architecture and experience with the HuggingFace ecosystem