11 hours ago
Sydney, Australia or Melbourne, AustraliaStaff+
Responsibilities
- Design and execute end-to-end AI systems, including data pipelines, ML pipelines, distributed training, and model-serving architectures.
- Provide deep technical support for go-to-market, pre-sales, post-sales, proofs of concept, bake-offs, hackathons, workshops, and technical demonstrations.
- Engage executives, data scientists, developers, DevOps teams, and IT leaders to explain Red Hat AI’s technical and business value.
- Move AI initiatives from experimentation to production by applying AI systems design and MLOps best practices.
- Advocate for Red Hat AI products and provide field feedback to Red Hat’s AI Business Unit and Engineering teams.
- Enable partners and internal teams on modern AI and ML architecture patterns across the region.
- Contribute to the technical community through conference speaking, technical blog posts, architectural blueprints, and volunteer technology communities.
Requirements
- 15+ years of enterprise architecture experience.
- 7+ years of hands-on experience in machine learning use-case development and MLOps in enterprise environments.
- Strong foundational and applied knowledge of deep learning architectures, including CNNs, RNNs, and LSTMs, with the ability to explain practical trade-offs.
- Proven experience designing and deploying generative AI architectures involving LLMs, prompt engineering, and fine-tuning strategies.
- Proficiency in Python and the end-to-end data science lifecycle.
- Proven ability to architect and explain complex data and ML pipelines, distributed training, and high-scale inference to technical and non-technical audiences.
- Exceptional presentation skills for business-value sessions and technical workshops with executives and engineering teams.
- Hands-on experience with Red Hat OpenShift AI and Red Hat AI Enterprise.
- Familiarity with open-source or open-weights models, model alignment, fine-tuning, LLMOps, and quantization.
- Deep understanding of inference optimization with vLLM and model-serving frameworks such as KServe and ModelMesh.
- Practical experience with Retrieval-Augmented Generation, agentic workflows, and vector databases.
- Expertise with PyTorch, TensorFlow, and the Jupyter ecosystem.
- A degree in Computer Science, Mathematics, or a related technical field is preferred.
Benefits
- The role is based in Sydney or Melbourne and covers customer engagements across Australia and New Zealand.
- Red Hat supports flexible work environments ranging from in-office to office-flex and fully remote depending on role requirements.
- Red Hat provides an inclusive, equal-opportunity workplace and reasonable accommodations for applicants with disabilities.
Tech Stack
Categories
Solutions Engineering
About Red Hat
Red Hat builds enterprise open-source software, including Red Hat Enterprise Linux, OpenShift for Kubernetes, and Ansible automation, sold via subscriptions with support, training, and consulting. It serves large enterprises and public-sector organizations running hybrid and multi-cloud infrastructure and modern application platforms. Founded in 1993 and headquartered in Raleigh, North Carolina, Red Hat operates as an independent subsidiary of IBM.