You will own well-defined components of AI projects, from data modeling and evaluation to infrastructure development. You will collaborate with engineers and domain experts to deploy reliable models and agents into production.
You will explore multimodal datasets to build features and pipelines while developing and testing models and agents under the guidance of senior staff. The role involves writing clean, production-ready code and continuously learning new methods as the field evolves.
You will lead end-to-end data science projects, scoping business problems and developing reliable AI models and agents. Additionally, you will mentor team members and communicate complex technical solutions to both technical and non-technical stakeholders.
You will build a real-time collaborative canvas product, focusing on direct manipulation, streaming AI output, and complex frontend state management. You will work closely with a small senior team to implement features like presence, optimistic updates, and conflict handling.
You will design, build, and maintain robust production data pipelines and data models to transform raw data into reliable datasets. Additionally, you will manage data warehouse infrastructure and implement monitoring and quality checks to ensure data dependability.
Design, develop, and productionise optimisation algorithms and decision-support tools across various industries. Collaborate with clients and cross-functional teams to translate operational challenges into scalable software components.
Design, develop, and productionise optimisation algorithms and decision-support tools across various industries. Collaborate with cross-functional teams to translate operational challenges into scalable software components and measurable value.
You will explore and prepare datasets while training and evaluating machine learning models under the guidance of senior scientists. Additionally, you will write and maintain production-ready Python code and contribute to the development of LLM-powered systems.
You will build, iterate, and deploy machine learning models while maintaining production pipelines and contributing to LLM-powered systems. Additionally, you will analyze large multimodal datasets to extract insights and write clean, production-quality Python code.
You will lead the technical direction for AI projects, including scoping problems, building training infrastructure, and shipping production-grade models. You are responsible for the end-to-end lifecycle of AI systems, from data curation and model selection to monitoring and debugging in production.
