AI Engineer

Sydney based

Financial services

$150-200k

Overview:

I am working with a leading financial services company, who are looking to bring on a highly skilled Generative AI Engineer to join their exciting AI practice. This role is an exciting opportunity for hands-on engineers who are passionate about building cutting-edge Generative AI products and tools, any experience doing this in the past is hugely beneficial (where you have taken the lead on the build and been hands on). You will play a pivotal role in the development of chatbots, intelligent agents, and GenAI tooling solutions, transforming the way financial services are delivered.

Key Responsibilities:

• Design & Build: Lead OR have experience where you have done the architecture, design, and development of Generative AI products, including but not limited to chatbots, intelligent agents, and custom AI tooling for financial applications. This is a key focus, ideally you have the hands on experience and previous examples / use cases of the builds you've done
• Model Development: Develop and optimize transformer models and other advanced machine learning architectures to power GenAI applications. This can be at an academic level but where you have rolled out into production.
• Integration & Deployment: Work closely with cross-functional teams to integrate AI solutions with existing systems and ensure seamless deployment in real-world environments.
• Collaboration & Innovation: Collaborate with data scientists, engineers, and business stakeholders to continuously improve AI systems and bring innovative AI solutions to market.

• Experience: in building Generative AI products, including chatbots, intelligent agents, and custom AI tooling.
• Technical Expertise: Deep expertise in transformer models (e.g., GPT, BERT, etc.) and hands-on experience with building, training, and optimizing these models.
• Programming Languages: Strong proficiency in Python, TensorFlow, PyTorch, or similar AI frameworks.
• Hands-On Development: Proven track record of being able to engineer the solution from scratch-writing code, training models, and deploying end-to-end systems.