Job Description
If you’re someone eager to build one of the first enterprise-grade LLMs that will automate and help both compliance and legal teams become more productive, freeing them from long, drawn-out manual tasks, then this is the company for you.
In the last two years, this business has developed an AI-powered platform that is set to transform the Regulation Technology space, a multi-billion-pound industry in the making. Even better, it’s a proudly Australian brand.
As an ML Engineer, this role will combine LLMs with search methods for databases. You’ll be optimising the platform to detect compliance risks in real-time, enabling enterprise businesses to sift through thousands of marketing assets daily.
With plans to enhance performance, they’re keen to speak to individuals with experience in RAG search methods and those who’ve worked with search engineering and search technologies.
Think ElasticSearch, Vespa, OpenSearch, or Claudette. If you have prior experience with these, alongside being a Python expert and have worked in a production environment building ML models, you’re already ticking the right boxes!
Key Qualifications:
- Strong expertise in machine learning or search engineering, with 3+ years of experience
- Proficient in Python, with an emphasis on clean and maintainable code
- Solid experience with search technologies such as Vespa or OpenSearch
- Deep understanding of machine learning models and methodologies
- Practical experience with database technologies, particularly PostgreSQL
- Proven success in implementing machine learning systems in production
Exceptional candidates will have:
- Experience with LLM/RAG architecture in a production environment
- Familiarity with DevOps, CI/CD tools, and AWS
- Data Engineering and FastAPI Frameworks experience
As a startup, if you've been in a similar environment, this will be an excellent opportunity for you to push the boundaries of AI and search technology, solving problems that will remain relevant for years to come.