Senior Machine Learning Engineer Role

4 days ago

Sydney Adelaide City Of Brisbane Melbourne Perth, Australia beBeeMachineLearning Full time $150,000 - $200,000
Machine Learning Engineer Position

We're seeking a seasoned Machine Learning Engineer to join our team and contribute to the development of our high-throughput Generative AI platform. As a key member of our global R&D team, you will play a critical role in designing and implementing pipelines, GPU infrastructure, and automation that transform cutting-edge research into production-ready features.

The successful candidate will work at the intersection of Generative AI and MLOps, partnering with researchers to bring new models from prototype to production and ensure they deliver meaningful value. Your work will have a direct and visible impact, enabling teams across the organization to deliver AI-powered features faster, more reliably, and at scale.

Main Responsibilities:
  • Generative AI & Inference:
    • Collaborate with researchers to develop and deploy new models, ensuring they meet production standards.
    • Design and maintain production pipelines for diffusion-based and related generative models.
    • Optimize 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 Terraform.
  • Platform Acceleration:
    • Support other teams in developing high-impact projects requiring deep ML expertise.
    • Develop shared tooling, reusable workflows, and architecture patterns to help teams build and ship faster.
    • Promote knowledge-sharing, best practices, and scalable solutions across the organization.
Requirements:
  • Generative AI Experience: Experience deploying diffusion-based or similar generative models into production and working with inference optimization techniques.
  • MLOps Expertise: Skilled in building automated, reliable workflows for training, deploying, and monitoring ML models at scale.
  • Infrastructure & Cloud: Hands-on with AWS, Kubernetes, Docker, and Terraform.
  • Performance & Efficiency: Proficient in techniques such as quantisation, distillation, caching, and distributed inference.
  • Data Foundations: Ability to design scalable data pipelines and storage solutions.
  • Engineering Craft: Strong Python skills and a focus on writing clear, maintainable, and collaborative code.
  • Collaboration & Growth: Thrive in cross-functional teams, value open feedback, and enjoy supporting others' success while learning continuously.
Our Culture:
  • Inclusive Environment: We celebrate diversity and are committed to creating an environment where everyone feels valued and empowered.
  • Flexible Work Arrangements: We understand the importance of work-life balance and offer flexible work arrangements.
  • Empowering Growth: Your development is our priority. We offer continuous learning opportunities and career growth tailored to your goals.
  • Impactful Work: Join us in shaping the future of AI. You'll work on innovative projects that have a meaningful impact, and your contributions will help drive advancements in AI creativity.

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