Overview
In this role you will shape transformative Generative AI strategies for clients, leading end-to-end design and deployment of cutting-edge AI pipelines. You will engage with senior stakeholders to align AI initiatives with business goals and mentor cross-functional teams to deliver robust, scalable solutions. You’ll stay current with AI research, integrating new technologies into client solutions and internal frameworks. The role offers exposure to international clients and a mission-driven culture focused on measurable impact and responsible deployment.
Pay / Benefits
- hybrid working in London
- career development
- wellbeing support
- flexible work arrangements
- internal mobility and learning
- collaborative culture
Responsibilities
- Engage with senior client stakeholders and internal leadership to define and deliver transformative AI/Generative AI strategies aligned with business goals.
- Lead the end-to-end design, development, and deployment of advanced AI pipelines (data acquisition, preprocessing, feature engineering, model development, evaluation, secure deployment at scale).
- Oversee development and operationalisation of state-of-the-art models (LLMs, diffusion models, and generative techniques) with focus on scalability, efficiency, and robustness.
- Stay at the forefront of AI/GAs research, evaluating emerging tech and integrating relevant advancements into client solutions and internal frameworks.
- Mentor and guide cross-functional AI teams, promoting knowledge sharing, reusable assets, and best practices for delivery excellence.
Key requirements
- PhD or equivalent in Computer Science, ML, AI, or related discipline (or strong equivalent).
- Extensive experience designing, developing, deploying enterprise-grade AI/ML solutions with team and stakeholder management.
- Deep domain expertise applying AI/Generative AI in regulated or data-rich industries (e.g., financial services, healthcare).
- Track record of thought leadership in AI/ML (patents, publications, or open-source contributions).
- Industry certifications (AWS/Google/Azure/IBM ML) and familiarity with relevant courses or tutorials are highly desirable.
- Expert Python proficiency and experience with PyTorch, TensorFlow, and generative libraries (LangChain, LangGraph).
- Strong understanding of LLMs, prompt engineering, RAG pipelines, vector databases, and secure, scalable deployments.
- Experience with MLOps/LLMOps, CI/CD for ML, model monitoring, governance; cloud platforms (AWS/Azure/GCP) and security practices.
- Excellent stakeholder management and ability to translate complex AI concepts for varied audiences.
- stakeholder management
- clear communication
- team leadership
- Python
- PyTorch
- TensorFlow
…
