Machine Learning Engineer

Overview

EML is a leading Workers Compensation and Personal Injury Claims Management business. Our goal is to help people get their lives back through ongoing support during their return-to-work journey. We continue to experience ongoing growth and now have over 4,000 dedicated employees. We foster a learning culture that allows for us to continually invest in our employees ensuring a long-term career here at EML.

The Opportunity

EML is at the forefront of the AI revolution, building innovative products that leverage the latest advancements in generative AI and large language models to solve real-world problems. We are a team of passionate engineers and researchers committed to pushing the boundaries of what's possible. To achieve our ambitious goals, we invest in top quality infrastructure. 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.

As a Machine Learning Engineer in our newly created inhouse AI team, you will be instrumental in taking our LLM and generative AI initiatives from research to production. You will design, build, and optimize scalable systems that serve millions of users, directly impacting our product and customers.

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.

This will be a full time, 12 month Contract position based in the Sydney office, with flexibility to work from home up to 3 days per week.

Your Responsibilities

• Work with the MLE team to design, train, and optimize AI models specialized in audio tasks, Computer Vision, and NLP tasks.
• Research and implement cutting-edge algorithms and techniques from the latest publications in the field.
• Optimize model performance and efficiency for inference and deployment in production environments.
• Collaborate with data engineers and MLOps engineers to build and maintain robust data pipelines for model training and evaluation.
• Conduct thorough testing and validation of models to ensure accuracy and stability.
• Work with MLOps/Cloud Engineer and contribute to the development of our machine learning infrastructure and best practices.

About You

• Master's/PhD's degree in Computer Science, or a related technical field.
• 3+ years of professional experience in ML engineering, or software development. At least 1+ years of work/hands-on experience working with Large Language Models (e.g., GPT, Llama, Mistral).
• Proven track record of productionising ML models and deploying scalable AI solutions on cloud platforms (AWS: SageMaker, EC2, Lambda).
• Strong foundational knowledge in NLP, Computer Vision, or Audio processing.
• Deep understanding of transformer architectures, attention mechanisms, and autoregressive models.
• 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 (LoRA, QLoRA).
• Practical experience with model optimization techniques, such as Quantization (GPTQ, AWQ, bitsandbytes), pruning, or knowledge distillation.

What We Offer

• A vibrant, collaborative innovative team culture
• Flexibility with opportunity to WFH when you are fully trained in your role.
• A corporate wellbeing program with discounted health insurance and gym membership
• Access to discounts at over 350 retailers through our Rewards Hub program
• Entitlement to an annual tenure and performance-based recognition reward
• Comprehensive learning and development support
• Companywide events to celebrate success.
• Quarterly Reward and Recognition Awards
• Up to 16 weeks paid parental leave, plus super

We value our people and are committed to supporting our employees by investing in their professional development and providing generous employee benefits. If this position is of interest to you, please apply now.

Seniority level

• Mid-Senior level

Employment type

• Full-time

Job function

• Engineering and Information Technology
• Industries

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