Engineer - Artificial Intelligence at PEXA Group

Melbourne, Victoria, Australia -

Full Time

Start Date

Immediate

Expiry Date

05 Jan, 26

Salary

0.0

Posted On

07 Oct, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Artificial Intelligence, Machine Learning, Deep Learning, Software Engineering, Natural Language Processing, Large Language Models, AWS Bedrock, Snowflake Cortex, Python, Java, C++, TensorFlow, PyTorch, Keras, Data Processing, DevOps

Industry

Information Services

Description

Hi, we’re PEXA We know you’ll Google us before applying, so we’ll keep this brief. Every time a house is bought, sold or refinanced in Australia your lawyer, conveyancer and lender will most likely use a digital platform to settle your property, this is where we come in. PEXA’s world-first digital settlement platform has revolutionised the way we exchange property in Australia helping over 20,000 people a week safely settle their homes. And this is just the beginning. Our data and insights are helping organisations unlock the intel they need to drive change and possibilities. We’re still growing, innovating and looking ahead, but behind our greatest achievements, there is a team of curious creators and big thinkers. That’s why, we’re looking for ambitious people like yourself to join the team. What you’ll be doing The AI Engineer is a critical role responsible for bridging the gap between AI research and practical application. This individual will leverage their expertise in machine learning, deep learning, and software engineering to build, deploy, and maintain robust and scalable AI systems. A core focus of this role is the development and deployment of applications powered by Large Language Models (LLMs). You will be involved in the full lifecycle of AI projects, from problem definition and data preparation to model development, testing, deployment, and monitoring. The ideal candidate is a proactive problem-solver with a strong technical foundation in both general AI/ML and specialised LLM expertise, a passion for AI innovation, and the ability to translate complex algorithms, including advanced language models, into real-world solutions. Experience with platforms like AWS Bedrock and Snowflake Cortex is highly desirable. \n Key Responsibilities Design and implement AI/ML models - including Large Language Models - to solve real business challenges. Build scalable, efficient AI systems and pipelines optimised for LLM workloads. Select and apply the right tools, frameworks, and platforms (e.g. AWS Bedrock, Snowflake Cortex). Write clean, testable code and apply best practices in LLM development and prompt engineering. Optimise model performance, scalability, and efficiency to meet enterprise demands. Prepare, manage, and secure data - from preprocessing to storage - for AI and LLM training. Deploy and integrate AI solutions across cloud, on-premise, and edge environments, including API development. Stay ahead of AI/LLM advancements, pilot new technologies, and identify innovative use cases. Collaborate with data scientists, engineers, and product teams, and communicate insights clearly to all audiences. Apply responsible AI practices, addressing bias, transparency, and compliance in all solutions What you’ll bring to the table Master's degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence, or a related field. Specialisation in Natural Language Processing or Machine Learning with a focus on LLMs is a plus. Demonstrated experience with Large Language Models (LLMs) and Natural Language Processing (NLP) is highly preferred. Proven experience with a range of machine learning algorithms (e.g., regression, classification, clustering, deep learning, NLP, computer vision), including experience with LLM architectures and techniques. Experience with deep learning frameworks such as TensorFlow, PyTorch, Keras, etc., especially in the context of NLP and LLMs. Experience with cloud platforms and deploying AI solutions in cloud environments is required, with specific experience on platforms like AWS Bedrock and Snowflake Cortex being a significant advantage. Strong programming skills in languages such as Python, Java, or C++, with proficiency in NLP libraries (e.g., spaCy, NLTK, Transformers library) essential. Experience with data processing and manipulation tools and libraries (e.g., Pandas, NumPy, Spark), particularly for text data processing. Familiarity with software engineering principles, DevOps practices, and version control systems (e.g., Git). Why join us? Quarterly wellness days to recharge Four weeks Workcation per year – work from an approved country Take the opportunity to purchase up to four weeks additional annual leave per year Learn from the best and upskill with PEXA Academy certifications and grow your career \n A career at PEXA starts with you! If you think you have the required skills, an appetite to learn and would be a great fit, we’d love to hear from you – even if you don’t tick all the boxes. At PEXA we support your growth and help you discover your full potential. Our commitment to our people and a better future PEXA is a workplace where everyone can contribute and participate, so that every person can reach their full potential. We want our people to feel equally valued, supported and celebrated. With market-leading benefits that make a difference, we’re committed to supporting individuals, families and carers. Your culture, gender, sexual orientation, language and other attributes make you unique! We couldn't be prouder to have a team that reflects the richness of our wider community. We’re a proud ‘Circle Back Initiative’ Employer and commit to responding to every applican Stay Connected If you like the sound of this role, then make a start today. We encourage people of all backgrounds to apply. You can learn more about life at PEXA on our website and social channels too.

Responsibilities

The AI Engineer will design and implement AI/ML models to solve business challenges and build scalable AI systems optimized for LLM workloads. This role involves the full lifecycle of AI projects, including model development, testing, deployment, and monitoring.