Lead AI Engineer

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Design, architect, and implement cutting-edge AI solutions utilizing advanced machine learning, generative AI, and agentic AI technologies.

• Promote the adoption of contemporary AI frameworks, best practices in AI Ops, and scalable cloud-native architectures.

• Provide hands-on technical guidance and leadership.

• Collaborate with clients to convert business challenges into reliable AI solutions.

• Ensure the application of responsible AI practices throughout the delivery of solutions.

• Mentor technical team members and encourage innovation, ongoing learning, and engineering excellence.

• Oversee, coach, and develop a small team of staff members.

• Manage employee performance and support career advancement.

• Offer direction and guidance for the team while addressing complex problems.

⛳️ Requirements

• A minimum of a 2.1 degree in Computer Science, AI, Data Science, Statistics, or a related quantitative discipline.

• Proven experience in deploying contemporary AI/ML solutions in production environments.

• Proficiency in prompt engineering, retrieval-augmented generation (RAG), model evaluation, and monitoring using metrics like precision, recall, NDCG, and drift detection.

• Strong skills in Python and a solid foundation in software engineering best practices, including CI/CD, testing, and code reviews.

• Experience in developing scalable solutions on Azure and AWS platforms.

• Familiarity with containerization and orchestration tools such as Kubernetes and Docker.

• Expertise in data engineering for AI, including handling large-scale, unstructured, and multimodal datasets.

• Knowledge of responsible AI principles, model interpretability, and ethical considerations.

• Excellent interpersonal skills with the ability to lead client projects and articulate requirements in non-technical terms.

• Experience in managing, coaching, and developing junior team members and community contributors.

• Demonstrable experience with modern deep learning frameworks like PyTorch and TensorFlow.

• Familiarity with fine-tuning or distillation of large language models such as GPT, Llama, Claude, and Gemini.

• Experience with machine learning libraries including scikit-learn and XGBoost.

• Knowledge of data storage for AI, vector databases, semantic search, and knowledge graphs.

• Contributions to open-source AI projects or publication of research work.

• Understanding of AI security, privacy, and compliance standards such as ISO 42001.

🏝️ Benefits

• A people-first culture that supports professional development.

• Recruitment accommodations and adjustments are available.

• Customized recruitment process that caters to individual needs through private discussions.