Senior AI Engineer - Build Production-Grade AI/ML Systems

Salt

Melbourne

In loco

AUD 120.000 - 180.000

Tempo pieno

14 giorni+

Una candidatura completa in un minuto

Curriculum e lettera di presentazione personalizzati, pronti da inviare.

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Descrizione del lavoro

Salt is seeking an experienced AI Engineer for our Operations Technology team in Melbourne. You will design, build, and support AI/ML solutions that enable innovation and business performance across a global environment.

You will deliver AI/ML projects end-to-end, design scalable software with Azure AI, OpenAI, and other platforms, and optimise RAG pipelines, embeddings, and inference workflows. Collaboration with engineers, analysts, and QA is essential.

Competenze

  • 3+ years' experience in machine learning, data science, or related fields.
  • 1-2 years in AI/MLOps.

Mansioni

  • Deliver AI/ML projects from concept through to production.
  • Design and implement scalable software solutions using Azure AI, OpenAI and other LLM platforms.
  • Build and optimise RAG pipelines, embeddings, fine-tuning, and inference workflows.
  • Collaborate with developers, analysts and testers to deliver reliable, secure, and maintainable applications.
  • Provide proactive application support, troubleshooting, and issue resolution.
  • Apply DevOps practices including CI/CD, containerisation, and automated testing.

Conoscenze

Machine learning
Data science
AI/MLOps
Python
SQL

Formazione

Bachelor's degree in Applied Mathematics / Machine Learning / Data Science / Software Engineering

Strumenti

Azure AI Foundry
Azure OpenAI
Cognitive Search
ML
Functions
OpenAI
Hugging Face
LangChain
LlamaIndex
Vector search tools

Descrizione del lavoro

Salt is seeking an experienced AI Engineer for our Operations Technology team in Melbourne. You will design, build, and support AI/ML solutions that enable innovation and business performance across a global environment.

You will deliver AI/ML projects end-to-end, design scalable software with Azure AI, OpenAI, and other platforms, and optimise RAG pipelines, embeddings, and inference workflows. Collaboration with engineers, analysts, and QA is essential.

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