AI Expertise Seeker

6 days ago

Sydney, New South Wales, Australia beBeeCareer Full time $150,000 - $180,000

AI Revolution Leader

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We are at the forefront of an exciting revolution in Artificial Intelligence, where we are building innovative products that leverage the latest advancements in generative AI and large language models to solve real-world problems.

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You will be working directly on our advanced GPU clusters, providing you with the computational power needed to train, fine-tune, and deploy cutting-edge models without constraint.

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Job Description

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As a Machine Learning Engineer in our newly created in-house AI team, you will be instrumental in taking our LLM and generative AI initiatives from research to production.

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You will design, build, and optimize scalable systems that serve millions of users, directly impacting our product and customers.

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This is a hands-on role for someone who is equally passionate about the theoretical foundations of deep learning and the engineering challenges of deploying efficient, reliable models at scale.

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Responsibilities

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Work with the MLE team to design, train, and optimize AI models specialized in audio tasks, Computer Vision, and NLP tasks.

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Research and implement cutting-edge algorithms and techniques from the latest publications in the field.

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Optimize model performance and efficiency for inference and deployment in production environments.

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Collaborate with data engineers and MLOps engineers to build and maintain robust data pipelines for model training and evaluation.

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Conduct thorough testing and validation of models to ensure accuracy and stability.

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Work with MLOps/Cloud Engineer and contribute to the development of our machine learning infrastructure and best practices.

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Requirements

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A Master's/PhD degree in Computer Science or a related technical field.

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At least 3 years of professional experience in ML engineering or software development.

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Strong foundational knowledge in NLP, Computer Vision, or Audio processing.

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Deep understanding of transformer architectures, attention mechanisms, and autoregressive models.

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Hands-on experience with the full lifecycle of LLM fine-tuning including Supervised Fine-Tuning (SFT), Reinforcement Learning from Human Feedback (RLHF), and parameter-efficient methods.

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Practical experience with model optimization techniques such as Quantization, pruning, or knowledge distillation.

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What We Offer

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A vibrant, collaborative innovative team culture.

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Flexibility with opportunity to work from home when fully trained in your role.

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A corporate wellbeing program with discounted health insurance and gym membership.

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Access to discounts at over 350 retailers through our Rewards Hub program.

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Entitlement to an annual tenure and performance-based recognition reward.

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Comprehensive learning and development support.

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Companywide events to celebrate success.

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Quarterly Reward and Recognition Awards.

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Up to 16 weeks paid parental leave, plus super.

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Why Choose Us?

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We value our people and are committed to supporting our employees by investing in their professional development and providing generous employee benefits.

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