AI Engineer

The Role

We are seeking a skilled and motivated AI Engineer to join a rapidly growing, innovative team. As a key technical contributor, you will collaborate with leadership to shape the technical vision and drive product development from the ground up. This hands-on position is ideal for someone with strong technical expertise, an entrepreneurial mindset, and the ability to develop scalable solutions. You will have the chance to build and evolve a product that addresses real-world challenges and contribute to the company’s strategic goals.

Responsibilities (including but not limited to):

• Work closely with cross-functional teams to identify business opportunities and design effective data-driven solutions.
• Develop, fine-tune, and deploy machine learning and deep learning models, including neural networks, to enhance platform intelligence and capabilities.
• Integrate advanced language models (LLMs) into the product pipeline, utilising techniques such as Retrieval-Augmented Generation (RAG) to improve data insights.
• Utilise LLM frameworks such as LangChain to build and manage workflows that adapt to changing data and user needs.
• Perform data analysis, processing, and feature engineering to support model development.
• Collaborate with engineering teams to integrate AI/ML solutions into the product and ensure scalability and reliability in deployment.
• Create and manage robust data pipelines, ensuring data integrity and compliance with industry standards.
• Conduct experiments, validate hypotheses, and iteratively refine models based on real-world feedback.
• Establish best practices in data science, AI/ML, and deep learning, setting standards for a growing data science team.

We’re looking for…

• An enthusiastic and dedicated individual with an entrepreneurial mindset, strong communication skills, and a collaborative approach to team-based work.
• Fluency in English and a minimum of 3-5 years of experience in data science, machine learning, AI, or deep learning (academic experience also considered).
• Strong proficiency in Python, with hands-on experience in machine learning and deep learning libraries such as Scikit-learn, TensorFlow, and PyTorch.
• Familiarity with key machine learning algorithms, including decision trees, gradient boosting, clustering, and neural networks.
• Practical experience deploying AI/ML models, particularly LLMs, utilising techniques such as RAG, fine-tuning, and prompt engineering.
• Experience with LLM frameworks like LangChain to enhance product functionality.
• Expertise in data analytics, statistical modelling, and predictive analytics.
• Solid understanding of SQL, with experience in relational and non-relational databases; familiarity with cloud data solutions (e.g., AWS Redshift, Azure Synapse) is a plus.
• Experience working with large datasets and frameworks like Spark and Airflow for data pipeline management.
• Knowledge of cloud platforms (AWS, Azure) and scalable infrastructure for AI/ML, deep learning, and LLM pipelines.
• Experience with natural language processing (NLP), LLM techniques like RAG, and generative AI applications.