Senior AI Engineer

The Hr Ally — Australia · Posted ~21 hours ago

Senior Full-time No Visa

Skills

AI/ML machine learning algorithms deep learning MLOps machine learning

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Summary ✨ AI‑Generated

A senior AI engineering position focused on designing, developing, and deploying machine learning solutions at scale. The role includes building AI pipelines, applying MLOps practices, and guiding technical direction for impactful projects.

Highlights

Leadership role developing advanced AI solutions, shaping technical strategy, and mentoring engineering teams.

Description

Role: Senior AI Engineer Location: Perth Job type: Permanent Eligibility: Australian PRs & Citizens only Transforming its business through Artificial Intelligence, bringing our unique culture of innovation and leading through doing to transform our asset and employee productivity. The responsibilities of this role is to lead AI solution design, development, and deployment. This role requires a deep understanding of AI/ML algorithms, scalable architectures, and MLOps best practices, with the ability to mentor junior team members and guide project strategy. Key responsibilities include: Lead the end-to-end lifecycle of AI projects—from data acquisition to deployment and monitoring. Design, build, and optimize complex ML/DL models, including large-scale and generative AI solutions. Architect scalable and maintainable AI pipelines using MLOps tools and practices. Collaborate with product managers, data scientists, and engineers to align AI solutions with business needs. Conduct code reviews, ensure best practices, and mentor junior engineers. Stay updated on emerging AI trends, tools, and research to drive innovation. Qualifications and Experience: Bachelor’s/Master’s degree in Computer Science, AI/ML, or related 5+ years of experience in AI/ML engineering or applied data science. Expertise in Python and frameworks like TensorFlow, PyTorch, and Scikit-learn. Strong knowledge of deep learning architectures (CNNs, RNNs, Transformers). Experience with LLMs and prompt engineering. Proficiency in deploying AI solutions on cloud platforms (AWS SageMaker, Azure ML, or GCP Vertex AI). Experience with MLOps tools (MLflow, Kubeflow, Docker, Kubernetes). Strong leadership, problem-solving, and communication skills.