2 months ago
Remote, United Kingdom +2 moreStaff+
Responsibilities
- Architect, design, and deliver advanced production-grade AI and machine learning solutions.
- Apply generative AI, agentic AI, prompt engineering, retrieval-augmented generation, model evaluation, and monitoring techniques.
- Drive adoption of modern AI frameworks, AI operations practices, and scalable cloud-native architectures.
- Develop AI solutions at scale on Azure and AWS using Kubernetes and Docker.
- Handle large-scale, unstructured, and multimodal data for AI applications.
- Lead client projects and translate business challenges into trustworthy AI solutions in non-technical language.
- Ensure responsible AI, model interpretability, security, privacy, and ethical practices throughout delivery.
- Manage, coach, and develop a small number of staff and provide direction and leadership for the team.
- Foster innovation, continuous learning, and engineering excellence.
Requirements
- A minimum of a 2.1 degree in Computer Science, AI, Data Science, Statistics, or a similar quantitative field.
- Demonstrable experience deploying modern AI and machine learning solutions into production.
- Experience with prompt engineering, retrieval-augmented generation, model evaluation, and monitoring metrics such as precision, recall, NDCG, and drift detection.
- Strong Python skills and grounding in software engineering best practices, including testing and code reviews.
- Experience developing scalable solutions on Azure and AWS with Kubernetes and Docker.
- Expertise in data engineering for large-scale, unstructured, and multimodal AI data.
- Understanding of responsible AI principles, model interpretability, and ethical considerations.
- Strong interpersonal skills and ability to lead client projects and establish requirements in non-technical language.
- Experience managing, coaching, and developing junior team members.
- Preferred experience with PyTorch, TensorFlow, LLM fine-tuning or distillation, GPT, Llama, Claude, Gemini, scikit-learn, and XGBoost.
- Preferred experience with data storage for AI, vector databases, semantic search, and knowledge graphs.
- Contributions to open-source AI projects or research publications are desirable.
- Familiarity with AI security, privacy, and compliance standards such as ISO42001 is desirable.
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