Data Scientist Machine Learning

1 week ago


Sydney, New South Wales, Australia beBeeArtificial Full time $275,000 - $350,000
AI Engineer Job Description

We are seeking an experienced AI Engineer to contribute to the design, development, and deployment of advanced AI models and systems that power intelligent products.

This is a great opportunity to work on high-impact AI initiatives at the forefront of technology.

Innovative Work:
  • Drive impactful AI and machine learning projects using state-of-the-art technologies, including Generative AI and Retrieval-Augmented Generation (RAG) systems.
  • Play a key role in developing next-generation AI-powered solutions.
Growth Opportunity:
  • Advance your career by contributing to AI strategy, collaborating with diverse teams, and tackling challenging problems that push the boundaries of machine learning in a fast-paced environment.
Collaborative Team:
  • Work alongside talented AI engineers, researchers, and product leaders in a dynamic setting that values innovation, expertise, and continuous learning.
Key Responsibilities:
  • Develop, train, and deploy large language models (LLMs) and machine learning solutions with real-world applications.
  • Build and maintain end-to-end AI pipelines, from data processing to production model serving.
  • Support and implement Retrieval-Augmented Generation (RAG) and multi-model orchestration features.
  • Collaborate closely with engineering, product, and data science teams to deliver scalable AI-powered features.
  • Evaluate emerging AI technologies and frameworks to continuously improve our AI capabilities.
Requirements:
  • 4+ years experience in AI/ML, with solid knowledge of LLMs, generative AI, and applied machine learning.
  • Hands-on experience building and deploying AI models in production.
  • Familiarity with RAG architectures, vector databases, and hybrid model workflows.
  • Strong programming skills in Python and experience with ML libraries (PyTorch, TensorFlow, Hugging Face, LangChain).
  • Understanding of cloud platforms and MLOps tools for scalable AI deployment (AWS, GCP, or Azure).
  • Effective communication and collaboration skills, with a passion for innovation and problem-solving.


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