Advanced Artificial Intelligence Engineering Professional

7 days ago

Sydney Adelaide City Of Brisbane Melbourne Perth, Australia beBeeMACHINELEARNING Full time $150,000 - $250,000

We're seeking an experienced Senior Machine Learning Engineer to help build and deliver high-throughput Generative AI platforms. You'll collaborate with researchers, engineers, and other teams to design and implement production-ready features, transforming cutting-edge research into scalable solutions.

As part of our global R&D team, you'll focus on deploying diffusion-based models into production, working with inference optimisation techniques, and building automated workflows for training, deployment, and monitoring ML models at scale.

This role requires a strong background in machine learning, software engineering, and cloud infrastructure, with experience in AWS, Kubernetes, Docker, and Infrastructure-as-Code tools like Terraform.

Key Responsibilities
  • Generative AI & Inference:
    • Collaborate with researchers to bring new models from prototype to production and ensure they deliver meaningful value.
    • Build and maintain production pipelines for diffusion-based models.
    • Optimise inference for speed, reliability, and efficiency using techniques such as quantisation, distillation, caching, and multi-GPU parallelism.
  • MLOps & Infrastructure:
    • Develop and maintain automated MLOps pipelines covering training, deployment, monitoring, and retraining.
    • Build CI/CD workflows for machine learning that make handovers from research to production seamless and safe.
    • Create scalable data pipelines and storage solutions to support high-throughput workloads.
    • Set up clear monitoring and alerting for model performance.
    • Design secure, reliable infrastructure on AWS using Infrastructure-as-Code tools.
  • Platform Acceleration:
    • Be embedded in other teams to support high-impact projects requiring deep ML expertise.
    • Develop shared tooling, reusable workflows, and architecture patterns that help teams build and ship faster.
    • Promote knowledge-sharing, best practices, and scalable solutions across the organisation.
Skills We Require
  • Experience with Generative AI: Deploying diffusion-based models into production and working with inference optimisation techniques.
  • MLOps Expertise: Building automated workflows for training, deployment, and monitoring ML models at scale.
  • Infrastructure & Cloud: Hands-on experience with AWS, Kubernetes, Docker, and Infrastructure-as-Code tools.
  • Performance & Efficiency: Proficient in techniques such as quantisation, distillation, caching, and distributed inference.
  • Data Foundations: Strong skills in designing scalable data pipelines and storage solutions (SQL/NoSQL).
  • Engineering Craft: Strong Python skills and a focus on writing clear, maintainable code.
  • Collaboration & Growth: Thrive in cross-functional teams, value open feedback, and enjoy supporting others' success while learning continuously.

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