Director - AI Engineering Lead

What you’ll do

• Lead a focused team to explore and harness the Generative AI capabilities.

• Design and execute Proof of Concepts (PoCs) to validate AI use cases.

• Develop and implement initial use cases that leverage Generative AI and Machine Learning technologies.

• Establish and oversee governance frameworks for AI applications to ensure compliance and ethical use.

• Collaborate with senior leadership to define the AI operating model and strategic direction.

• Foster a culture of ideation and innovation within the Axial team, encouraging exploration of new innovative technologies and methodologies.

• Architect and implement generative AI models tailored to produce structured outputs such as text or images.

• Research and apply advanced machine learning algorithms to improve model efficiency and accuracy.

• Create user-friendly applications using Streamlit

• Handle large datasets, perform data cleaning, and apply feature engineering to prepare data for model training.

• Work collaboratively with cross-functional teams to understand requirements and translate them into technical solutions.

• Optimize and fine-tune GPT models to improve output quality and efficiency.

• Conduct research and stay up to date with the latest advancements in AI, machine learning, and NLP to integrate new methodologies into existing processes.

• Debug and resolve issues in AI models and the associated infrastructure.

• Document technical specifications and processes to support ongoing development and enhancements.

• Support the deployment and integration of AI solutions into existing systems.

Essential for the role

• 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.

• Proficiency in using Streamlit to create interactive and visually appealing web applications.

• Extensive experience in software development including full SDLC

• Experience of developing and integrating applications using APIs

• Solid understanding of natural language processing (NLP) techniques and applications.

• Experience using computer vision techniques

• Experience with machine learning frameworks and libraries (TensorFlow, PyTorch, etc.).

• Strong software development skills, including python and scala. Experience with automation strategies (CI/CD etc) and containerisation (Kubernetes, Docker) is key.

• Excellent problem-solving skills and attention to detail.

• Excellent written and verbal communication, business analysis, and consultancy skills