Director - AI Engineering Lead

What you’ll do

1. Lead a focused team to explore and harness the Generative AI capabilities.
2. Design and execute Proof of Concepts (PoCs) to validate AI use cases.
3. Develop and implement initial use cases that leverage Generative AI and Machine Learning technologies.
4. Establish and oversee governance frameworks for AI applications to ensure compliance and ethical use.
5. Collaborate with senior leadership to define the AI operating model and strategic direction.
6. Foster a culture of ideation and innovation within the Axial team, encouraging exploration of new innovative technologies and methodologies.
7. Architect and implement generative AI models tailored to produce structured outputs such as text or images.
8. Research and apply advanced machine learning algorithms to improve model efficiency and accuracy.
9. Create user-friendly applications using Streamlit
10. Handle large datasets, perform data cleaning, and apply feature engineering to prepare data for model training.
11. Work collaboratively with cross-functional teams to understand requirements and translate them into technical solutions.
12. Optimize and fine-tune GPT models to improve output quality and efficiency.
13. Conduct research and stay up to date with the latest advancements in AI, machine learning, and NLP to integrate new methodologies into existing processes.
14. Debug and resolve issues in AI models and the associated infrastructure.
15. Document technical specifications and processes to support ongoing development and enhancements.
16. Support the deployment and integration of AI solutions into existing systems.

Essential for the role

1. At least 5 years’ experience demonstrating technical skills in one or more of the following areas: Generative AI, machine learning, recommendation systems, pattern recognition, natural language vision or computer vision.
2. Proficiency in using Streamlit to create interactive and visually appealing web applications.
3. Extensive experience in software development including full SDLC
4. Experience of developing and integrating applications using APIs
5. Solid understanding of natural language processing (NLP) techniques and applications.
6. Experience using computer vision techniques
7. Experience with machine learning frameworks and libraries (TensorFlow, PyTorch, etc.).
8. Strong software development skills, including python and scala. Experience with automation strategies (CI/CD etc) and containerisation (Kubernetes, Docker) is key.
9. Excellent problem-solving skills and attention to detail.
10. Excellent written and verbal communication, business analysis, and consultancy skills

Desirable for the role

1. Prior experience in Azure AI stack
2. Knowledge of large language models like GPT, Claude, Gemini.
3. Experience with version control systems like Git.
4. Knowledge of agents and multi-agent systems, including agent-based modelling and simulation.
5. Familiarity with decision-making algorithms and systems that exhibit goal-directed behaviour.
6. Strong foundation in linear algebra, calculus, probability, and statistics.
7. Ability to apply mathematical concepts to optimize models and interpret results
8. Experience of multi-cloud cloud platform (AWS, Azure, GCP) is an advantage. Azure as primary experience
9. Proficient working in high performance computing or cloud environment
10. Experience in translating requirements into fit for purpose models, processing designs, data mappings and data profile reports
11. Experience in working relevant domains e.g. Pharma, R&D, Manufacturing, Commercial, Finance, HR, Legal, Facilities etc.