You will work closely with data, product, and engineering teams to develop scalable AI systems and integrate models into production environments.
Key Responsibilities
Design, develop, and deploy machine learning and AI models for production use
Build and maintain scalable data pipelines and model-serving infrastructure
Train, evaluate, and optimise models for performance, accuracy, and efficiency
Work with large datasets to extract insights and improve model outcomes
Collaborate with product and engineering teams to translate business needs into AI solutions
Monitor, test, and iterate on models in live environments
Ensure best practices around model performance, reliability, and security
Required Skills & Experience
Strong experience in Python and common ML libraries (TensorFlow, PyTorch, scikit-learn)
Solid understanding of machine learning fundamentals and algorithms
Experience deploying models to production environments (cloud or on-prem)
Familiarity with data processing tools and pipelines
Understanding of model evaluation, optimisation, and monitoring techniques
Nice to Have
Experience with large language models (LLMs) or generative AI
Knowledge of MLOps tools and workflows
Experience working with cloud platforms (AWS, GCP, Azure)
Background in applied research or experimentation