Design and implement AI/ML models - including Large Language Models - to solve real business challenges.
Build scalable, efficient AI systems and pipelines optimised for LLM workloads.
Select and apply the right tools, frameworks, and platforms (e.g. AWS Bedrock, Snowflake Cortex).
Write clean, testable code and apply best practices in LLM development and prompt engineering.
Optimise model performance, scalability, and efficiency to meet enterprise demands.
Prepare, manage, and secure data - from preprocessing to storage - for AI and LLM training.
Deploy and integrate AI solutions across cloud, on-premise, and edge environments, including API development.
Stay ahead of AI/LLM advancements, pilot new technologies, and identify innovative use cases.
Collaborate with data scientists, engineers, and product teams, and communicate insights clearly to all audiences.
Apply responsible AI practices, addressing bias, transparency, and compliance in all solutions
Requirements
Master's degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence, or a related field. Specialisation in Natural Language Processing or Machine Learning with a focus on LLMs is a plus.
Demonstrated experience with Large Language Models (LLMs) and Natural Language Processing (NLP) is highly preferred.
Proven experience with a range of machine learning algorithms (e.g., regression, classification, clustering, deep learning, NLP, computer vision), including experience with LLM architectures and techniques.
Experience with deep learning frameworks such as TensorFlow, PyTorch, Keras, etc., especially in the context of NLP and LLMs.
Experience with cloud platforms and deploying AI solutions in cloud environments is required, with specific experience on platforms like AWS Bedrock and Snowflake Cortex being a significant advantage.
Strong programming skills in languages such as Python, Java, or C++, with proficiency in NLP libraries (e.g., spaCy, NLTK, Transformers library) essential.
Experience with data processing and manipulation tools and libraries (e.g., Pandas, NumPy, Spark), particularly for text data processing.
Familiarity with software engineering principles, DevOps practices, and version control systems (e.g., Git).
Benefits
Quarterly wellness days to recharge
Four weeks Workcation per year – work from an approved country
Take the opportunity to purchase up to four weeks additional annual leave per year
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