About the Company :

An Australia-based technology company focused on building innovative cloud-based software solutions for the accounting and auditing industry. The organization develops modern SaaS products that help businesses streamline workflows, automate processes, improve compliance, and manage operations efficiently.

The company works with modern technologies including cloud computing, automation, integrations, and AI-enabled solutions, delivering scalable products for businesses across Australia.

What You'll Do :

- Design, develop, and deploy AI/ML models and solutions for real-world business applications.

- Build and maintain machine learning pipelines for data preparation, model training, evaluation, and deployment.

- Work with Python and popular ML frameworks to develop scalable AI solutions.

- Develop and integrate AI/ML models and APIs into cloud-based applications.

- Work with structured and unstructured data to identify patterns and build predictive solutions.

- Collaborate with engineering and product teams to integrate AI capabilities into applications.

- Monitor model performance and continuously improve accuracy and reliability.

- Stay updated with advancements in Generative AI, LLMs, and machine learning technologies.

Basic Qualifications :

- Minimum 3+ years of experience in AI/ML Engineering or Machine Learning.

- Strong hands-on experience with Python.

- Good experience with Machine Learning algorithms, model development, and evaluation.

- Experience with frameworks such as PyTorch, TensorFlow, or Scikit-learn.

- Good understanding of NLP, Generative AI, or LLMs.

- Experience developing and integrating REST APIs for AI/ML solutions.

- Good understanding of data preprocessing, feature engineering, and model optimization.

- Experience with SQL and databases.

- Exposure to cloud platforms such as AWS, Azure, or GCP.

- Good understanding of Git and software development practices.

Preferred Skills :

- Experience with LLMs, RAG, Prompt Engineering, or LangChain.

- Knowledge of MLOps and ML model deployment.

- Experience with Docker and CI/CD pipelines.

- Exposure to Vector Databases and AI application development.

- Experience working with SaaS / cloud-based products.