Partner with data scientists, engineers, and stakeholders across the organization to define high-impact solutions and deliver high-quality systems and data pipelines.
Building, training & iterating on data science, machine learning & artificial intelligence models.
Develop prototypes based on cutting-edge applied machine learning, working with different data modalities.
Own the technical translation of state-of-the-art machine learning innovations to inform the development of new product features.
Productionise and operate ML models and data pipelines at scale.
Design and implement well-defined APIs for new machine learning tools to make them available for customers and engineering teams across the organisation.
Design and implement machine learning infrastructure capabilities.
Reviewing and validating scalable data collection and processing methods.
Tracking and understanding emergent trends.
Sourcing and leveraging external research/data that strengthen our internal insights.
Requirements & Skills:
Deep expertise in software engineering and machine learning engineering, gained from prior experience working on a production engineering team
Strong backend engineering ability and understanding of engineering best practices (CI/CD, version control, cloud environments, observability, configuration management)
In-depth experience with Python and strong command of databases (e.g. PostgreSQL), data structures, and algorithms
In-depth knowledge of one or more of the major machine learning frameworks (e.g., PyTorch or TensorFlow).
Ability to manage machine learning projects and clearly communicate outcomes to technical and non-technical audiences.
Experience with MLFlow, Metaflow, and/or LangChain
Working knowledge of the education/skills sector
Understanding of AI ethics, data protection, and information security
