Job Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.
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Key Responsibilities
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Design, build, and optimize robust machine learning models for production environments.
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Implement and automate end-to-end ML pipelines using CI/CD best practices.
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Leverage AWS services for scalable AI infrastructure and model deployment.
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Orchestrate containerized workloads using Kubernetes to ensure high availability and seamless scalability.
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Collaborate with data scientists, engineers, and researchers to translate complex business problems into actionable ML solutions.
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Evaluate, preprocess, and frame real-world data problems for effective machine learning applications.
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Document and communicate findings, solution approaches, and technical decisions with clarity and precision.
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Required Skills And Qualifications
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Proven expertise in machine learning algorithms, model development, and deployment.
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Solid programming skills, ideally in Python or Java, with experience in large-scale software engineering projects.
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In-depth experience with CI/CD workflows and automation tools.
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Hands-on expertise with AWS cloud services for ML applications and data pipelines.
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Advanced knowledge of Kubernetes for orchestrating containerized ML workloads.
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Exceptional written and verbal communication skills, with a focus on clear technical documentation and team collaboration.
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Demonstrated ability to scope, structure, and solve complex, real-world data challenges.
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Preferred Qualifications
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Familiarity with deep learning frameworks such as TensorFlow or PyTorch.
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Experience working in high-growth or startup settings.
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Solid publication record or contributions to open-source AI projects.
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📌 Remote Ai Engineer Build Scalable Ml Pipelines New South Wales (Australia)
🏢 YO IT CONSULTING
📍 Australia
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